WO2014132490A1 - Vehicle specifications measurement processing device, vehicle specifications measuring method, and recording medium - Google Patents
Vehicle specifications measurement processing device, vehicle specifications measuring method, and recording medium Download PDFInfo
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- WO2014132490A1 WO2014132490A1 PCT/JP2013/079255 JP2013079255W WO2014132490A1 WO 2014132490 A1 WO2014132490 A1 WO 2014132490A1 JP 2013079255 W JP2013079255 W JP 2013079255W WO 2014132490 A1 WO2014132490 A1 WO 2014132490A1
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/04—Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/015—Detecting movement of traffic to be counted or controlled with provision for distinguishing between two or more types of vehicles, e.g. between motor-cars and cycles
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30236—Traffic on road, railway or crossing
Definitions
- the present invention relates to a vehicle specification measurement processing device, a vehicle specification measurement method, and a recording medium, and more particularly, to a vehicle specification measurement processing device, a vehicle specification measurement method, and a recording medium, and more particularly to a vehicle specification (width, length).
- the present invention relates to an apparatus and a method for measuring the height.
- Tollgates such as expressways and toll roads may be provided with a vehicle type discriminating device for discriminating the type of vehicle passing through.
- vehicle type discriminating device for discriminating the type of vehicle passing through.
- Various methods are used for vehicle type discrimination. In recent years, it has been studied to take an image of a vehicle and perform vehicle type discrimination using the taken image. Since various information about the vehicle can be obtained from the vehicle image, the vehicle type determination using the vehicle image is useful for increasing the accuracy of the vehicle type determination.
- a feature point may be extracted from the vehicle image, and the vehicle type may be determined based on the extracted feature point.
- Non-Patent Document 1 J Prokai, G Medoni, “3-D model based vehicle recognition,” Applications of Computer Vision (WACV), 2009
- CG computer graphic
- a technique is disclosed in which a database in which a template created is registered in advance is prepared, and a vehicle type is estimated by matching processing between a feature point extracted from an image and a database template.
- the vehicle specifications for example, width, length, height
- the calculated vehicle specification is information for discriminating the vehicle type.
- Patent Document 1 Japanese Patent Application Laid-Open No. 11-86185
- Patent Document 1 Japanese Patent Application Laid-Open No. 11-86185
- the contact position between the tire and the road surface is detected, and the position and the approach angle in the three-dimensional space of the vehicle are calculated from the contact position and the installation conditions of the photographing device.
- The By correcting the image obtained by photographing the vehicle based on the calculated position and approach angle of the vehicle in the three-dimensional space, a geometric correction image of the front and side of the vehicle is generated, and the vehicle is generated from the generated geometric correction image. Is estimated.
- Non-Patent Document 2 (A. Lai, G. Fung and N. Yung, “Vehicle type classification from visual-based dimension estimation” IEEE, Intelligent Transportation Systems, pages 201-206, 2001) is the appearance of the vehicle in the image. Discloses a technique for estimating the specifications of a vehicle from the size of the vehicle. Specifically, in the technique disclosed in Non-Patent Document 2, a region corresponding to the outer shape of the vehicle is extracted as a hexagonal region from the image. Among the hexagonal vertices, the coordinates of the three vertices near the road surface are calculated, the vehicle width and length are calculated from the coordinates, and the vehicle height is the height direction in real space. Is calculated from the length of the side of the hexagon corresponding to.
- an object of the present invention is to provide a technique capable of calculating vehicle specifications (for example, width, length, height) by robust image processing for feature point detection.
- a vehicle specification measuring device includes an imaging device that sequentially captures a vehicle to obtain a frame image of the vehicle, and an image processing device that calculates the width of the vehicle based on the frame image. is doing.
- the image processing apparatus includes, for at least one of the frame images, a first feature measurement feature point that is a feature point on the first surface of a rectangular parallelepiped that approximates the shape of the vehicle, and a feature point that is on the second surface of the rectangular parallelepiped.
- Feature point detecting means for detecting the second feature measurement feature point and the third feature measurement feature point that is the feature point on the third surface of the rectangular parallelepiped, and the first feature measurement feature point
- Vehicle feature calculation means for calculating the width of the vehicle based on the second feature measurement feature point and the third feature measurement feature point.
- the first surface is a rectangular parallelepiped surface corresponding to the first side surface of the vehicle
- the second surface is a rectangular parallelepiped surface corresponding to the second side surface of the vehicle
- the third surface is the lower surface of the vehicle.
- the vehicle specification calculation means calculates the movement amount of the vehicle from the movement amount of the third feature measurement feature point, and uses the vehicle movement amount to determine the first feature measurement feature point and the second feature measurement feature.
- 3D coordinates of the first feature measurement feature point and the second feature measurement feature point are calculated by performing motion stereo processing on the point, and the calculated first feature measurement feature point and second The vehicle width is calculated from the three-dimensional coordinates of the feature measurement feature points.
- the position of the first feature measurement feature point detected by the feature point detection means has a degree of freedom in the plane of the first surface
- the position of the second feature measurement feature point detected by the feature point detection means has a degree of freedom in the plane of the second surface.
- the position of the third feature measurement feature point detected by the feature point detection means has a degree of freedom in the plane of the third surface.
- the feature point detection unit extracts a moving area corresponding to the vehicle from the frame image, and extracts a tangent line that is a line in the frame image corresponding to the line that contacts the vehicle in the real space. Then, the intersection point on the first surface among the intersection points of the extracted tangent lines may be determined as the first feature measurement feature point.
- the feature point detection means may be configured to determine an intersection point on the second surface among the intersection points of the extracted tangent lines as the second feature measurement feature point. Of these, the intersection point on the third surface may be determined as the third feature measurement feature point.
- the feature point detection unit extracts a moving area corresponding to the vehicle from the frame image, and extracts a tangent line that is a line in the frame image corresponding to the line that contacts the vehicle in the real space.
- the feature point for measuring the first item may be determined by searching for the feature point along the first search path constituted by the portion on the first surface of the extracted tangent line.
- the feature point detecting means determines the second feature measurement feature point by searching for the feature point along the second search path constituted by the portion on the second surface of the extracted tangent line.
- the feature point detecting means may be configured to measure the third feature by searching for a feature point along a third search path constituted by a portion on the third surface of the extracted tangent line. It may be configured to determine feature points.
- the feature point detection means includes a first template of a component assumed to exist on the first side surface of the vehicle, and first feature point position data indicating the position of the feature point in the first template. You may have a database.
- the feature point detecting means obtains a first matching position that is a position of the first template that most closely matches the frame image by template matching with the template of the first template database, and the first matching position and the first feature point are obtained.
- the first feature measurement feature point may be detected as the first feature measurement feature point at the position determined from the position data.
- the feature point detecting means has a second template database including a second template of a part assumed to exist on the second side surface of the vehicle and second feature point position data indicating the position of the feature point in the second template. You may do it.
- the feature point detection means obtains a second matching position that is the position of the second template that most closely matches the frame image by template matching with the second template of the second template database, and determines the second matching position and the second matching position.
- the second feature measurement feature point may be detected on the assumption that the feature feature for second feature measurement exists at the position determined from the feature point position data.
- the feature point detection means has a third template database including a third template of parts assumed to be present on the lower surface of the vehicle and third feature point position data indicating the position of the feature point in the third template. May be.
- the feature point detection means obtains a third matching position that is the position of the third template that most closely matches the frame image by template matching with the third template of the third template database, and determines the third matching position and the third matching position.
- the third feature measurement feature point may be detected by assuming that there is a feature feature for third feature measurement at a position determined from the feature point position data.
- a vehicle specification measuring device includes a photographing device that sequentially photographs a vehicle to obtain a frame image of the vehicle, and an image processing device that calculates the length of the vehicle based on the frame image. It has.
- the image processing apparatus has a third feature measurement feature point that is a feature point on the third surface of a rectangular parallelepiped that approximates the shape of the vehicle and a feature point on the fourth surface of the rectangular parallelepiped for at least one of the frame images.
- Feature point detecting means for detecting the fourth feature measurement feature point and the fifth feature measurement feature point which is the feature point on the fifth surface of the rectangular parallelepiped, and the third feature measurement feature point
- Vehicle feature calculation means for calculating the length of the vehicle based on the fourth feature measurement feature point and the fifth feature measurement feature point.
- the third surface is a cuboid surface corresponding to the lower surface of the vehicle
- the fourth surface is a cuboid surface corresponding to the front surface of the vehicle
- the fifth surface is a cuboid surface corresponding to the rear surface of the vehicle.
- the vehicle specification calculation means calculates the vehicle movement amount from the movement amount of the third feature measurement feature point, and uses the vehicle movement amount to calculate the fourth feature measurement feature point and the fifth feature measurement feature.
- the three-dimensional coordinates of the fourth feature measurement feature point and the fifth feature measurement feature point are calculated, and the calculated fourth feature measurement feature point and fifth feature point are calculated.
- the length of the vehicle is calculated from the three-dimensional coordinates of the feature measurement feature points.
- the position of the third feature measurement feature point detected by the feature point detection means has a degree of freedom within the third plane.
- the position of the fourth feature measurement feature point detected by the feature point detection means has a degree of freedom in the plane of the fourth surface, and the position of the fifth feature measurement feature point detected by the feature point detection means.
- a vehicle specification measuring device captures a vehicle sequentially and acquires a frame image of the vehicle, and an image processing device calculates the height of the vehicle based on the frame image. It comprises.
- the image processing apparatus includes a third feature measurement feature point that is a feature point on a third surface of a rectangular parallelepiped approximating the shape of the vehicle and a feature point on a sixth surface of the rectangular parallelepiped for at least one of the frame images.
- Feature point detecting means for detecting the sixth feature measurement feature point, and the vehicle feature for calculating the height of the vehicle based on the third feature measurement feature point and the sixth feature measurement feature point.
- a calculating means is a third feature measurement feature point that is a feature point on a third surface of a rectangular parallelepiped approximating the shape of the vehicle and a feature point on a sixth surface of the rectangular parallelepiped for at least one of the frame images.
- the third surface is a rectangular parallelepiped surface corresponding to the lower surface of the vehicle
- the sixth surface is a rectangular parallelepiped surface corresponding to the upper surface of the vehicle.
- the vehicle specification calculation means calculates the vehicle movement amount from the movement amount of the third feature measurement feature point, and uses the vehicle movement amount to calculate the third feature measurement feature point and the sixth feature measurement feature. By performing motion stereo processing on the point, three-dimensional coordinates of the third feature measurement feature point and the sixth feature measurement feature point are calculated, and the calculated third feature measurement feature point and sixth feature point are calculated.
- the vehicle height is calculated from the three-dimensional coordinates of the feature measurement feature points.
- the position of the third feature measurement feature point detected by the feature point detection means has a degree of freedom in the plane of the third surface, and the position of the sixth feature measurement feature point detected by the feature point detection means. Has a degree of freedom in the plane of the sixth surface.
- a vehicle specification measurement method includes: Capturing the vehicle sequentially to obtain a frame image of the vehicle; For a frame image, a first feature measurement feature point that is a feature point on the first surface of the rectangular parallelepiped approximating the shape of the vehicle, and a second feature measurement feature point that is a feature point on the second surface of the rectangular parallelepiped. Detecting a third feature measurement feature point that is a feature point on the third surface of the rectangular parallelepiped; Calculating the width of the vehicle based on the first feature measurement feature point, the second feature measurement feature point, and the third feature measurement feature point.
- the first surface is a rectangular parallelepiped surface corresponding to the first side surface of the vehicle
- the second surface is a rectangular parallelepiped surface corresponding to the second side surface of the vehicle
- the third surface is the lower surface of the vehicle.
- the position of the first feature measurement feature point detected in the detection step has a degree of freedom in the plane of the first surface, and the position of the second feature measurement feature point detected in the detection step. Has a degree of freedom in the plane of the second surface. Further, the position of the third feature measurement feature point detected in the detecting step has a degree of freedom within the third surface.
- a vehicle specification measurement method includes: Capturing the vehicle sequentially to obtain a frame image of the vehicle; For at least one of the frame images, a third feature measurement feature point that is a feature point on the third surface of the cuboid that approximates the shape of the vehicle, and a fourth feature point that is a feature point on the fourth surface of the cuboid. Detecting an original measurement feature point and a fifth feature measurement feature point that is a feature point on the fifth surface of the rectangular parallelepiped; Calculating the length of the vehicle based on the third feature measurement feature point, the fourth feature measurement feature point, and the fifth feature measurement feature point.
- the third surface is a cuboid surface corresponding to the lower surface of the vehicle
- the fourth surface is a cuboid surface corresponding to the front surface of the vehicle
- the fifth surface is a cuboid surface corresponding to the rear surface of the vehicle.
- the step of calculating the length of the vehicle is: Calculating a movement amount of the vehicle from a movement amount of the third feature measurement feature point;
- the fourth feature measurement feature point and the fifth feature measurement feature are obtained by performing motion stereo processing on the fourth feature measurement feature point and the fifth feature measurement feature point using the movement amount of the vehicle.
- Calculating the three-dimensional coordinates of the point Calculating the length of the vehicle from the calculated three-dimensional coordinates of the fourth feature measurement feature point and the fifth feature measurement feature point.
- the position of the third feature measurement feature point detected in the detecting step has a degree of freedom within the third surface. Further, the position of the fourth feature measurement feature point detected in the detection step has a degree of freedom in the plane of the fourth surface, and the fifth feature measurement feature point detected in the detection step. Has a degree of freedom in the plane of the fifth surface.
- a vehicle specification measurement method includes: Capturing the vehicle sequentially to obtain a frame image of the vehicle; For at least one of the frame images, a third feature measurement feature point that is a feature point on the third surface of the cuboid that approximates the shape of the vehicle, and a sixth feature point that is the feature point on the sixth surface of the cuboid. Detecting original measurement feature points; Calculating the height of the vehicle based on the third feature measurement feature point and the sixth feature measurement feature point.
- the third surface is a rectangular parallelepiped surface corresponding to the lower surface of the vehicle
- the sixth surface is a rectangular parallelepiped surface corresponding to the upper surface of the vehicle.
- the step of calculating the height of the vehicle is Calculating a movement amount of the vehicle from a movement amount of the third feature measurement feature point;
- the third feature measurement feature point and the sixth feature measurement feature are obtained by performing motion stereo processing on the third feature measurement feature point and the sixth feature measurement feature point using the movement amount of the vehicle.
- the position of the third feature measurement feature point detected in the detection step has a degree of freedom in the plane of the third surface, and the position of the sixth feature measurement feature point detected in the detection step is There is a degree of freedom in the plane of the sixth plane.
- the vehicle specification measurement method described above may be performed by the arithmetic device executing a program.
- the program may be installed in the arithmetic device using a recording medium on which the program is recorded.
- it is a conceptual diagram which shows the position of the feature point for item measurement used for measurement of the width
- it is a conceptual diagram which shows the position of the feature point for item measurement used for measurement of the length of a vehicle.
- it is a conceptual diagram which shows the position of the feature point for item measurement used for measurement of the height of a vehicle.
- It is a block diagram which shows the example of the hardware constitutions of the vehicle item measurement processing apparatus in one Embodiment.
- It is a flowchart which shows the image process for calculating the item of a vehicle in this embodiment.
- It is a flowchart which shows the image process for calculating the item of a vehicle in this embodiment.
- FIG. 1 it is a figure which shows the procedure which detects the feature point for item measurement in the front surface of a vehicle, and a rear surface from the tangent and intersection which were calculated
- FIG. 1 it is a figure which shows the procedure which detects the feature point for item measurement in the upper surface of a vehicle from the tangent and intersection which were calculated
- region in this embodiment. It is. In this embodiment, it is a figure which shows the procedure which detects the feature point for item measurement in the upper surface of a vehicle by searching a feature point along the search path decided by the tangent and intersection which were calculated
- images of a traveling vehicle are sequentially taken (that is, vehicle images are taken at different times), and feature points are detected and tracked for the plurality of images. Furthermore, motion stereo processing is performed on the feature points. Motion stereo processing is to capture an image of a moving object at different times, calculate the moving distance of the object by some method (may be calculated from the captured image itself), This is a technique for calculating the three-dimensional coordinates of an object in the three-dimensional coordinates that move with the object from the movement distance of the object.
- the three-dimensional coordinates of the object can be calculated by a method similar to general stereo processing from the information that the position of the object differs by the movement distance.
- the three-dimensional coordinates of the feature points are calculated by motion stereo processing, and the specifications of the vehicle are calculated from the three-dimensional coordinates.
- One feature of the measurement processing of the vehicle specifications in the present embodiment is a feature point extraction technique used for calculating the width, length, and height of the vehicle.
- 1A to 1C are diagrams showing feature points used for measuring the width, length, and height of a vehicle, respectively.
- a rectangular parallelepiped 30 that approximates the outer shape of the vehicle is defined, and the feature points at positions along a specific surface of the rectangular parallelepiped 30 are used as feature points used for measuring the width, length, and height of the vehicle. Is done. Note that the rectangular parallelepiped 30 is virtually determined.
- symbols v 1 to v 8 represent vertices of the rectangular parallelepiped 30.
- feature points used for measuring the width, length, and height of the vehicle are (feature points (feature points for moving object detection) used for detecting a moving object from an image, as will be described later). For the sake of distinction, hereinafter, it will be referred to as feature measurement feature points.
- Feature measurement feature point # 1 feature point on the side surface 31 of the vehicle (strictly, a feature point at a position along the surface of the rectangular parallelepiped 30 corresponding to the side surface 31 of the vehicle)
- Feature measurement feature point # 2 Feature point on the side surface 32 of the vehicle (strictly, feature point located along the surface of the rectangular parallelepiped 30 corresponding to the side surface 32 of the vehicle
- Feature measurement feature point # 3 A feature point on the lower surface 33 of the vehicle (strictly, a feature point at a position along the surface of the rectangular parallelepiped 30 corresponding to the lower surface 33 of the vehicle)
- the side surface 31 is the side surface of the two side surfaces of the vehicle that faces the camera that measures the traveling vehicle
- the side surface 32 is the other side surface.
- the surface of the cuboid 30 corresponding to the side surface 31 has vertices v 1 to v 4 , and the surface of
- the feature measurement feature points # 1, # 2, and # 3 are allowed to be extracted from arbitrary positions as long as the conditions that the feature points # 1, # 2, and # 3 are on the side surfaces 31, 32 and the lower surface 33 are satisfied.
- a feature point at an arbitrary position on the side surface 32 is used as a feature measurement feature point # 2.
- feature points extracted from arbitrary positions of the contour of the vehicle along the sides v 5 v 6 and v 6 v 7 are the side surfaces 32. It will be used as a feature point above.
- a feature point at an arbitrary position on the lower surface 33 is allowed to be used as the feature measurement feature point # 3.
- the feature points extracted from arbitrary positions of the contour of the vehicle along the sides v 3 v 7 and v 3 v 4 are actually lower surface 33. It will be used as a feature point above.
- the feature measurement feature point # 3 on the lower surface 33 is used to calculate the moving distance of the vehicle. Furthermore, motion stereo processing is performed for the feature measurement feature points # 1 and # 2 using the calculated moving distance, and the feature measurement feature points # 1 and # 2 in the three-dimensional coordinate system moving with the vehicle. Three-dimensional coordinates (for example, relative coordinates with respect to the feature measurement feature point # 3) are calculated, and the width of the vehicle is calculated from the calculated three-dimensional coordinates of the feature measurement feature points # 1 and # 2.
- Feature measurement feature point # 3 Feature point on the lower surface 33 of the vehicle
- Feature measurement feature point # 4 Feature point on the front surface 34 of the vehicle (strictly, the surface of the rectangular parallelepiped 30 corresponding to the front surface 34 of the vehicle)
- Feature points located along Feature measurement feature point # 5 feature point on the rear surface 35 of the vehicle (strictly, a feature point at a position along the surface of the rectangular parallelepiped 30 corresponding to the rear surface 35 of the vehicle)
- the feature measurement feature points # 4 and # 5 are extracted from arbitrary positions as long as the condition that the feature measurement feature points # 4 and # 5 are on the front surface 34 and the rear surface 35 is satisfied as in the feature measurement feature points # 1 to # 3. Is acceptable. However, the positions of the feature points that are actually extracted differ depending on the arrangement of the cameras. When the camera is arranged so as to photograph the traveling vehicle from behind, the rear surface 35 faces the camera. In this case, for the rear surface 35, the feature point at an arbitrary position on the rear surface 35 is allowed to be used as the feature measurement feature point # 5, while the front surface 34 that is actually hidden in the vehicle.
- FIG. 1B shows such a camera arrangement.
- the front surface 34 faces the camera.
- a feature point at an arbitrary position on the front surface 34 is allowed to be used as a feature measurement feature point # 4, while the rear surface 35 that is actually hidden in the vehicle.
- feature points extracted from an arbitrary position on the contour of the vehicle along the side that can be photographed from the camera will be used as feature measurement feature points # 5 on the rear surface 35.
- motion stereo processing is performed on the feature measurement feature points # 4 and # 5 using the travel distance of the vehicle calculated based on the feature measurement feature point # 3 on the lower surface 33. Done. Thereby, the three-dimensional coordinates of the feature measurement feature points # 4 and # 5 in the three-dimensional coordinate system moving with the vehicle (for example, the relative coordinates with respect to the feature measurement feature point # 3) are calculated. The length of the vehicle is calculated from the three-dimensional coordinates of the feature measurement feature points # 4 and # 5.
- Feature measurement feature point # 3 feature point on the lower surface 33 of the vehicle (strictly, a feature point at a position along the surface of the rectangular parallelepiped 30 corresponding to the lower surface 33 of the vehicle)
- Feature measurement feature point # 6 feature point on the upper surface 36 of the vehicle (strictly, a feature point at a position along the surface of the rectangular parallelepiped 30 corresponding to the upper surface 36 of the vehicle)
- the feature measurement feature point # 6 is allowed to be extracted from an arbitrary position as long as it satisfies the condition of being on the upper surface.
- the camera is usually installed above the vehicle (for example, installed in a gantry provided on the road), so that the entire upper surface 36 of the vehicle is usually photographed. Please note that.
- the height of the vehicle In calculating the height of the vehicle, motion stereo processing is performed on the feature measurement feature point # 6 using the vehicle movement distance calculated based on the feature measurement feature point # 3 on the lower surface 33. As a result, the three-dimensional coordinates of the feature measurement feature points # 3 and # 6 in the three-dimensional coordinate system moving with the vehicle (for example, relative coordinates with respect to the feature measurement feature point # 3) are calculated, and the calculated specifications are calculated. The height of the vehicle is calculated from the three-dimensional coordinates of the original measurement feature points # 3 and # 6.
- FIG. 2 is a block diagram showing an example of the configuration of the vehicle specification measurement processing apparatus 10 of the present embodiment.
- the vehicle specification measurement processing device 10 includes a camera 1 and an image processing device 2.
- the camera 1 is an imaging device that captures a vehicle traveling on a road.
- the camera 1 generates image data 21 of a vehicle image (frame image) and supplies the generated image data 21 to the image processing device 2.
- the image processing device 2 performs image processing on the image data 21 received from the camera 1 and the specifications of the vehicle captured in the image of the image data 21, more specifically, the width, length of the vehicle, The height is measured, and vehicle specification data 22 indicating the width, length, and height of the vehicle is generated.
- the image processing apparatus 2 includes an image processing IC (integrated circuit) 3, an external interface 4, an external storage device 5, a memory 6, and a ROM (read only memory) 7.
- the external interface 4 is connected to the camera 1 and supplies the image data 21 received from the camera 1 to the image processing IC 3.
- the external storage device 5 stores data generated in the image processing in the image processing device 2.
- Data stored in the external storage device 5 includes vehicle specification data 22.
- the memory 6 is used as a working area for arithmetic processing by the image processing IC 3.
- the ROM 7 stores a program executed by the image processing IC 3.
- the program stored in the ROM 7 includes a vehicle specification measurement processing program 7a that is a program for executing image processing for measuring vehicle specifications.
- the configuration of the image processing apparatus 2 for calculating the vehicle specifications from the image data 21 is described.
- the image processing apparatus 2 also performs vehicle type determination using the vehicle specification data 22. It may be broken.
- a program necessary for vehicle type determination may be installed in the ROM 7.
- a rewritable nonvolatile memory such as a flash memory
- the vehicle specification measurement processing program 7a (and a program used for determining the vehicle type if necessary) may be installed in the ROM 7 from the outside.
- a recording medium storing the vehicle specification measurement processing program 7a may be used.
- an apparatus for accessing the recording medium is provided in the image processing apparatus 2.
- an appropriate storage device for example, a hard disk drive (HDD) or a solid state drive
- the image processing IC 3 includes an arithmetic module 11, an image input interface 12, a data input / output interface 13, a memory controller 14, and a ROM controller 15.
- the arithmetic module 11, the image input interface 12, the data input / output interface 13, the memory controller 14, and the ROM controller 15 are connected by an internal bus 16.
- the calculation module 11 executes the vehicle specification measurement processing program 7 a while using the memory 6 as a working area, and performs image processing for calculating vehicle specifications from the image data 21.
- the image input interface 12 is an interface that receives image data 21 from the camera 1.
- the data input / output interface 13 is an interface for accessing the external storage device 5.
- the memory controller 14 is an interface for accessing the memory 6.
- the ROM controller 15 is an interface for accessing the ROM 7.
- 3A and 3B are flowcharts showing image processing for calculating vehicle specifications in one embodiment of the present invention.
- the above-mentioned vehicle specification measurement processing program 7a is a program code group for executing this image processing.
- Image processing for calculating vehicle specifications is roughly divided into the following three stages: 1. Detection and tracking of feature points for moving object detection (steps S01 to S04 in FIG. 3A) 2. Detection and separation of moving objects, and detection and tracking of feature points for measurement (Steps S05 to S07 in FIG. 3A) 3. Calculation of vehicle specifications based on feature measurement feature points (steps S08 to S12 in FIG. 3B)
- each stage will be described in detail.
- step S01 image data 21 of a frame image obtained by photographing a vehicle is sequentially captured.
- Step S02 image data 21 of a frame image obtained by photographing a vehicle is sequentially captured.
- step S03 feature points included in the frame image shown in the image data 21 are detected, and each feature point is tracked.
- the feature points detected and tracked in step S03 do not necessarily match the above-described feature measurement feature points. Therefore, in order to distinguish from feature measurement feature points, the feature points detected and tracked in step S03 are hereinafter referred to as moving object detection feature points.
- a moving object detection feature point list 23 which is a list in which the detected and tracked moving object detection feature points are listed, is generated.
- the moving object detection feature point is added to the moving object detection feature point list 23.
- the moving object detection feature point that has disappeared outside the image or the moving object detection feature point that has failed to be tracked is removed from the moving object detection feature point list 23.
- step S02 The capturing of the image data 21 (step S02) and the detection and tracking of the moving object detection feature point (step S03) are sequentially performed until an end signal is given to the image processing apparatus 2.
- step S04 the image processing in the image processing apparatus 2 is ended.
- moving object detection feature points listed in the moving object detection feature point list 23 that is, currently tracked
- the feature point corresponding to each vehicle is detected from the moving object detection feature points.
- feature points corresponding to the vehicle that is, feature points excluding feature points not corresponding to the vehicle
- step S05 More specifically, among the moving object detection feature points listed in the moving object detection feature point list 23, the stationary feature points and the movements that are different from the movements of the vehicle are shown.
- the feature points are removed. Since the vehicle traveling on the road generally moves in the direction of the road, it is possible to determine that a feature point that does not move is a feature point that does not correspond to the vehicle.
- FIG. 4 is a diagram showing an example of detection of moving feature points in step S05.
- the feature point 41 is detected in the series of images, and the tracking is performed for the moving feature point 41.
- the feature points 41 that are being tracked are connected to each other by line segments.
- the feature points determined to be stationary are removed from the moving object detection feature point list 23.
- feature points satisfying the following conditions (1) to (3) are detected as moving feature points corresponding to the vehicle: (1) that it can track over a predetermined number N STD more consecutive frame images (the predetermined number N STD is given as a parameter).
- the size of a vector connecting the start point (the position where tracking of the feature point is started on the image) and the current point (that is, the latest position of the feature point on the image) is ⁇ ⁇ N Be TRC or higher.
- ⁇ is a predetermined parameter value (technically means a threshold of movement amount per unit time)
- NTRC is a frame image for which tracking is performed for the feature point. Is a number.
- the angle formed by the vector from the start point to the current point and the vector from the start point to the vanishing point of the image is equal to or less than a predetermined threshold angle.
- the vanishing point of the image here means a vanishing point defined in the perspective view when the image of the vehicle is approximated to the perspective view.
- the vanishing point 43 is illustrated on the right side of FIG.
- the right diagram of FIG. 4 shows an example of the moving feature points detected in step S05.
- the right diagram in FIG. 4 illustrates feature points 42a, 42b, and 42c that are tracked over a predetermined number of consecutive frame images.
- reference numeral 42a-1 indicates the start point of the feature point 42a
- reference numeral 42a-3 indicates the current point of the feature point 42a.
- Reference numeral 42a-2 indicates the position of the feature point 42a in the frame image between the frame image corresponding to the start point and the frame image corresponding to the current point.
- reference numeral 42b-1 indicates the start point of the feature point 42b
- reference numeral 42b-3 indicates the current point of the feature point 42b.
- Reference numeral 42b-2 indicates the position of the feature point 42b in the frame image between the frame image corresponding to the start point and the frame image corresponding to the current point. Further, reference numeral 42c-1 indicates the start point of the feature point 42c, and reference numeral 42c-3 indicates the current point of the feature point 42c. Reference numeral 42c-2 indicates the position of the feature point 42c in the frame image between the frame image corresponding to the start point and the frame image corresponding to the current point.
- Step S05 clustering of the detected moving feature points is performed.
- Step S06 this clustering is performed based on the distance from each feature point to vanishing point 43 and the direction of the vector from the start point to the current point.
- the distance to the vanishing point 43 of the feature points (in FIG. 5, it is shown as the distance D M) distance from the current point to the vanishing point 43 may be used, vanishing point from the start point 43 May be used, or an average distance between tracking feature points may be used.
- this clustering a group of feature points corresponding to one vehicle is classified into the same cluster.
- FIG. 5 shows an example of clustering in step S06.
- feature points 42a, 42b, 42c, 42d, 42e, and 42f are extracted in step S05.
- the distance to the vanishing point 43 and the direction of the vector from the start point to the current point are calculated.
- the distance to the vanishing point 43 in FIG. 5 each of the feature points is defined as the distance D M from the current point to the vanishing point 43, also the direction of the vector from the start point to the current point, the image from the horizontal direction It is defined as an angle.
- the distance from the current point 42a-3 to the vanishing point 43 and the angle ⁇ between the vector from the start point 42a-1 to the current point 42a-3 and the horizontal direction of the screen are calculated.
- the distance from the current point to the vanishing point 43 and the direction of the vector from the start point to the current point are calculated.
- clustering of the feature points 42a, 42b, 42c, 42d, 42e, and 42f is performed.
- the feature points 42a, 42b, and 42c are classified into clusters corresponding to the first vehicle
- the feature points 42d, 42e, and 42f are classified into clusters corresponding to the second vehicle. Will be.
- Step S07 After clustering of moving feature points, moving regions corresponding to each vehicle are extracted from the image, and further, feature-measurement feature points are detected and tracked for each moving region. (Step S07).
- a moving area that is an area where the vehicle is photographed in each image is extracted from the moving feature points of each cluster.
- a moving area is extracted for each cluster.
- the moving area is extracted as a polygonal area corresponding to the contour of the vehicle in the image.
- the moving region is extracted so that the moving feature point of each cluster becomes the vertex of the polygon.
- the above-described process for detecting feature points for measurement and the process of tracking are performed for the movement region corresponding to each vehicle.
- the feature measurement feature points # 1 and # 2 are feature points on the side surfaces 31 and 32 of the vehicle, respectively, and the feature measurement feature point # 3. Is a feature point on the lower surface 33 of the vehicle.
- the feature measurement feature point # 4 is a feature point on the front surface 34 of the vehicle, and the feature measurement feature point # 5 is a feature point on the rear surface 35 of the vehicle.
- feature measurement feature point # 6 is a feature point on the upper surface 36 of the vehicle. It should be noted that the number of feature measurement feature points # 1 to be extracted is not necessarily limited to one, and a plurality of feature measurement feature points # 1 may be extracted. The same applies to the other feature measurement feature points # 2 to # 6.
- the tracking of the feature point for specification measurement may be performed by a method of detecting the feature point for specification measurement of each frame image and associating the feature point for specification measurement between the frame images.
- tracking of feature measurement feature points is performed by detecting feature measurement feature points for a frame image (initial frame image) in which a moving region first appears, and for the feature measurement feature points in subsequent frame images. It may be performed by a technique for tracking a moving object.
- the process for detecting the feature points for specification measurement is performed at least for the initial frame, first, the process for detecting the feature points for specification measurement will be described first.
- the process of detecting feature measurement feature points is performed using at least one of the following methods (1) to (3).
- the number of feature measurement feature points # 1 to be extracted is not necessarily limited to one, and a plurality of feature measurement feature points # 1 may be extracted. Therefore, a plurality of feature measurement feature points # 1 may be extracted by using a plurality of the following methods (1) to (3). The same applies to the other feature measurement feature points # 2 to # 6.
- Method (1) In the method (1) of detecting feature measurement feature points, a tangent line that contacts each vehicle is extracted and an intersection point at which the tangent line intersects is obtained. The feature measurement feature points are selected and determined from the obtained intersections.
- “tangent” means a line in the image corresponding to a tangent that contacts the vehicle in real space.
- FIG. 7A and FIG. 7B show an example of processing for obtaining tangent lines that contact the vehicle and their intersections.
- the tangent may be a tangent tangent to the moving region in the image (tangent indicated by reference numerals 61 to 66), but is not necessarily limited thereto (for example, tangent indicated by reference numerals 67 to 69).
- a tangent 61 corresponding to a line that is on the road surface and parallel to the lane. , 62 are extracted.
- the angle at which a line on the road surface and parallel to the lane is captured in the image is determined by the spatial arrangement of the camera 1, and is information that is known in advance. Using this fact, a tangent corresponding to a line on the road surface and parallel to the lane is extracted.
- the tangent 61 is a tangent on the near side of the vehicle (when viewed from the camera 1) among the tangents corresponding to the line parallel to the extracted lane, and the tangent 62 is on the far side of the vehicle. A tangent.
- a tangent corresponding to a line that is on the road surface and is perpendicular to the lane is extracted in the real space.
- the angle at which the line perpendicular to the lane is captured in the real space is determined by the spatial arrangement of the camera 1 and is known in advance. is there.
- a tangent corresponding to a line perpendicular to the lane in the real space is extracted.
- the tangent 63 is a tangent on the near side of the vehicle (when viewed from the camera 1) among the tangents corresponding to the line perpendicular to the extracted lane, Tangent line 64 is a tangent line on the other side of the vehicle.
- intersection 51 of the tangent 61 and the tangent 63 is obtained, and the intersection 52 of the tangents 62 and 64 is obtained.
- a tangent corresponding to a line that is perpendicular to the road surface in the real space is extracted. Since the angle perpendicular to the road surface in the real space is captured in the image is information that is known in advance, this fact is used to correspond to the line perpendicular to the lane in the real space. The tangent line of the moving area can be extracted.
- the tangents on the far side of the vehicle are indicated by reference numeral 65, and the front side of the vehicle
- the tangent lines at 66 are indicated by reference numerals 66 and 67.
- the tangent 67 is extracted as a line passing through the intersection 51 of the tangents 61 and 63 on the front side of the vehicle.
- intersection point 56 is determined.
- a line that is located above the road surface in real space is in a plane parallel to the road surface, and is perpendicular or parallel to the lane.
- Tangent lines 68 and 69 corresponding to are extracted.
- the tangent 68 is a tangent corresponding to a line perpendicular to the lane
- the tangent 69 is a tangent corresponding to a line parallel to the lane.
- the tangent line 68 is extracted as a line passing through the intersection point 56.
- an intersection point 57 of the tangent lines 67 and 68 is obtained, and the tangent line 69 is extracted as a line passing through the intersection point 57.
- FIG. 8A to 8C are diagrams showing a method for determining each feature measurement feature point from the obtained intersections.
- FIG. 8A is a diagram showing a method for determining feature measurement feature points # 1 and # 2 on the side surfaces 31 and 32 of the vehicle and feature measurement feature point # 3 on the lower surface 33 of the vehicle.
- FIG. 8B is a diagram showing a method for determining the feature measurement feature point # 4 on the front surface 34 of the vehicle and the feature measurement feature point # 5 on the rear surface 35 of the vehicle.
- FIG. 8C is a diagram illustrating a method of determining the feature measurement feature point # 6 on the upper surface 36 of the vehicle. The method for determining the feature measurement feature point # 3 on the lower surface 33 of the vehicle is illustrated not only in FIG. 8A but also in FIGS. 8B and 8C.
- feature measurement feature # 1 is selected from the intersections on the side surface 31 of the vehicle (that is, intersections 51, 53, 54, and 57) among the intersections obtained as described above.
- all of the intersection points 51, 53, 54, 57 may be determined as the feature measurement feature point # 1, or one or more appropriately selected from the intersection points 51, 53, 54, 57. May be determined as feature measurement feature point # 1.
- the feature measurement feature point # 2 is selected from the intersection points (that is, the intersection points 52, 55, and 56) on the side surface 32 of the vehicle.
- all of the intersection points 52, 55, and 56 may be determined as the feature measurement feature point # 2
- one or a plurality of intersection points appropriately selected from the intersection points 52, 55, and 56 may be determined.
- the original measurement feature point # 2 may be determined.
- the feature measurement feature point # 3 is selected from the intersection points (that is, the intersection points 51, 53, 55) on the lower surface 33 of the vehicle.
- all of the intersection points 51, 53, and 55 may be determined as the feature measurement feature point # 3, and one or more intersection points appropriately selected from the intersection points 51, 53, and 55 may be determined.
- the original measurement feature point # 3 may be determined.
- the feature measurement feature point # 4 is selected from the intersection points (that is, the intersection points 52, 53, 54) on the front surface 34 of the vehicle.
- all of the intersection points 52, 53, and 54 may be determined as the feature measurement feature point # 4, and one or more intersection points appropriately selected from the intersection points 52, 53, and 54 may be determined.
- the original measurement feature point # 4 may be determined.
- the feature measurement feature point # 5 is selected from the intersection points (that is, the intersection points 51, 55, 56, 57) on the rear surface 35 of the vehicle.
- all of the intersection points 51, 55, 56, 57 may be determined as the feature measurement feature point # 5, and one or more appropriately selected from the intersection points 51, 55, 56, 57. May be determined as feature measurement feature point # 5.
- the feature measurement feature point # 6 is selected from the intersection points (that is, the intersection points 52, 56, 57) on the upper surface 36 of the vehicle.
- all of the intersection points 52, 56, and 57 may be determined as the feature measurement feature point # 6, and one or a plurality of intersection points appropriately selected from the intersection points 52, 56, and 57 may be determined.
- the original measurement feature point # 6 may be determined.
- Method (2) In the method (2) for detecting feature measurement feature points, the tangent and intersection are obtained in the same manner as in the method (1), and then the feature points are searched along the search path determined by the obtained tangent and intersection. Thus, feature points that are easier to track are searched for for each surface. The feature points obtained by this search are determined as feature measurement feature points.
- 9A to 9C are diagrams showing a method for determining each feature measurement feature point in the method (2).
- the route constituted by the portion on the side surface 31 of the tangent lines obtained as described above is determined as the search path.
- the feature points are searched for around the search path.
- the intersection is used to obtain a portion of the tangent line on the side surface 31 when determining the search path. More specifically, a portion connecting the intersection 54 and the intersection 53 in the tangent 65, a portion connecting the intersection 53 and the intersection 51 in the tangent 62, and the intersection 51 and the intersection 57 in the tangent 67.
- a search for feature points is performed around the search path formed by the connecting portions.
- the feature point obtained by this search is determined as feature measurement feature point # 1.
- the number of feature measurement feature points # 1 to be determined may be one or plural.
- a route constituted by a portion on the side surface 32 of the obtained tangent lines is determined as a search route, and a feature point search is performed around the search route. Is done. More specifically, feature points are searched for in the vicinity of a search path constituted by a portion connecting the intersection point 55 and the intersection point 56 in the tangent line 66 and a portion connecting the intersection point 56 and the intersection point 52 in the tangent line 62. Is called.
- the feature point obtained by this search is determined as feature measurement feature point # 2.
- the number of feature measurement feature points # 2 to be determined may be one or plural.
- a route constituted by a portion on the lower surface 33 of the obtained tangent lines is determined as a search route, and features around the search route are characterized.
- a point search is performed. More specifically, feature points are searched for in the vicinity of a search path constituted by a portion connecting the intersection 53 and the intersection 51 in the tangent 61 and a portion connecting the intersection 51 and the intersection 55 in the tangent 63. Is called.
- the feature point obtained by this search is determined as feature measurement feature point # 2.
- the number of feature measurement feature points # 2 to be determined may be one or plural.
- the route constituted by the portion on the front surface 34 among the tangent lines obtained as described above is the search path.
- a search for feature points is performed around the search path. More specifically, feature points are searched for in the vicinity of a search path constituted by a portion connecting the intersection 53 and the intersection 54 in the tangent 65 and a portion connecting the intersection 54 and the intersection 52 in the tangent 64. Is called.
- the feature point obtained by this search is determined as feature measurement feature point # 4.
- the number of feature measurement feature points # 4 to be determined may be one or plural.
- a route constituted by a portion on the rear surface 35 among the obtained tangent lines is determined as a search route, and feature points around the search route are feature points.
- Search is performed. More specifically, a portion connecting the intersection point 55 and the intersection point 56 in the tangent line 66, a portion connecting the intersection point 56 and the intersection point 57 in the tangent line 68, a portion connecting the intersection point 57 and the intersection point 51 in the tangent line 67, and A search for feature points is performed around the search path formed by the portion connecting the intersection 51 and the intersection 55 in the tangent line 63.
- a feature point obtained by this search is determined as feature measurement feature point # 5.
- the number of feature measurement feature points # 5 to be determined may be one or plural.
- a route constituted by a portion on the upper surface 36 of the obtained tangent lines is determined as a search path.
- a feature point search is performed around the search path. More specifically, feature points are searched for in the vicinity of the search path composed of a portion connecting the intersection 57 and the intersection 56 in the tangent line 68 and a portion connecting the intersection 56 and the intersection 52 in the tangent line 62. Is called.
- the feature point obtained by this search is determined as feature measurement feature point # 6.
- the number of feature measurement feature points # 6 to be determined may be one or plural.
- Method (3) In the method (3) for detecting feature measurement feature points, search for feature points is performed directly on each surface of the vehicle (that is, without referring to tangents and intersections as obtained in the above method (1)). Is done. The feature points obtained by this search are determined as feature measurement feature points. 10 to 11 are diagrams showing a method for determining feature measurement feature points in the method (3).
- FIG. 10 is a diagram conceptually illustrating an example of the contents of a prepared template database.
- the prepared database of templates includes the following six databases: A template database 71 including a template of parts on the side surface 31 on the camera side A template database 72 containing the template of the part on the side 32 opposite the camera A template database 73 containing the template of the part on the lower surface 33 A template database 74 containing the template for the part on the front 34 A template database 75 containing the template of the part on the rear surface 35 A template database 76 containing the template of the part on the upper surface 36 In each of the template databases 71 to 76, feature point position data indicating the position of the feature point in the template is attached to the template of each part.
- templates created from images of parts eg, tires, windows, mirrors, lights
- the positions of feature points are specified for each template. Is done. Black points in FIG. 10 indicate feature points defined in each template.
- a plurality of templates are prepared for each part in the template database 71.
- templates created from images of parts assumed to be on each surface are registered, and feature points are designated for each template.
- the template databases 71 to 76 are stored in appropriate storage means, for example, the external storage device 5 shown in FIG.
- FIG. 11 is a diagram conceptually illustrating detection of feature points for specification measurement by template matching.
- FIG. 11 illustrates detection of feature measurement feature point # 5 on the rear surface 35 using a template registered in the template database 75.
- the entire processing target frame image is subjected to matching processing with a template included in the template database 75 (that is, a component template on the rear surface 35).
- a template included in the template database 75 that is, a component template on the rear surface 35.
- Similarity is obtained for each template for each position of each frame image, and for each part, the most matching template and the position (matching position) of the template are calculated.
- the position of the feature measuring feature point is determined from the position of the template that best matches and the position of the feature point designated by the feature point position data for the template. According to such a procedure, feature measurement feature points are detected.
- Detecting feature measurement feature points by the above methods (1) to (3) may be performed for each frame image.
- tracking of feature measurement feature points is also performed by a method of associating feature measurement feature points between frame images.
- Detecting feature measurement feature points by the above methods (1) to (3) may be performed on a frame image (initial frame image) in which a moving region first appears.
- moving object tracking is performed on the detected feature measurement feature points using an appropriate algorithm.
- the detection and tracking of the characteristic measurement feature points in step S07 are performed as described above.
- the feature measurement feature points are detected and tracked in step S07, that is, the various features in the frame image at each time are detected.
- Data indicating the position of the original measurement feature point is recorded in the specification measurement feature point list 24.
- the feature measurement feature point list 24 is recorded in an appropriate storage means (for example, the external storage device 5 in FIG. 2).
- the feature measurement feature point list 24 is generated for each moving region every time the moving region appears in the image.
- FIG. 3B is a diagram conceptually illustrating the detection of entry and exit of the processing area of the vehicle.
- a specific area of each frame image (for example, an area defined at the bottom of the frame image) is defined as the processing area 44, and when the entire moving area corresponding to each vehicle enters the processing area 44, and A time point when the user leaves the processing area 44 is detected.
- the time when the entire vehicle enters the processing area 44, and The vehicle specification data 22 indicating the specification of the vehicle is calculated using the history data about the time between the time of exiting the processing area 44 (step S13).
- the calculation of the vehicle specification data 22 is performed by calculating the position of the feature measurement feature point in the frame image at each time between the time when the entire vehicle enters the processing area 44 and the time when the vehicle leaves the processing area 44. This is done by performing motion stereo processing on the data.
- the motion stereo processing calculates the three-dimensional coordinates of the feature measurement feature points at each time (strictly speaking, the three-dimensional coordinates of the three-dimensional coordinates that move with the vehicle), and obtains the vehicle specifications from the three-dimensional coordinates. It is done.
- 13A and 13B are conceptual diagrams illustrating motion stereo processing for obtaining the three-dimensional coordinates of each feature measurement feature point in the present embodiment.
- the moving amount d C of the vehicle in the real space is calculated from the moving amount in the frame image of the feature measurement feature point # 3 on the lower surface 33 of the vehicle. Is done.
- the correspondence between the movement amount of the point on the real space road surface in the frame image and the movement amount of the point in the real space can be obtained in advance based on the spatial arrangement of the camera 1.
- the feature measurement feature point # 3 on the lower surface 33 of the vehicle can be approximated from the amount of movement in the frame image of the feature point # 3 (which can be approximated to a point on the road surface in real space).
- the amount of movement d C of the point # 3 in the real space can be calculated.
- the motion stereo process is performed based on the premise that the feature measurement feature points # 1 to # 6 are moved by the calculated movement amount d C. That is, three-dimensional coordinates of the specification for measurement feature points # 1 to # 6 are calculated by the motion stereo process performed as specifications for measurement feature points # 1 to # 6 are moved by the movement amount d C.
- the vehicle specifications that is, the width, length, and height of the vehicle are calculated using the three-dimensional coordinates.
- the width of the vehicle is calculated from the three-dimensional coordinates of the feature measurement feature points # 1 and # 2 on the side surfaces 31 and 32, as shown in FIG. 1A.
- the length of the vehicle is calculated from the three-dimensional coordinates of the feature measurement feature points # 4 and # 5 on the front surface 34 and the rear surface 35.
- the height of the vehicle is calculated from the three-dimensional coordinates of the feature measurement feature points # 3 and # 6 on the lower surface 33 and the upper surface.
- vehicle specification data 22 indicating the calculated vehicle specifications is generated.
- the vehicle specification data 22 is stored in the external storage device 5.
- the calculated vehicle specifications are output using an appropriate output device (for example, a display device) (step S11), and the feature measurement feature point list 24 corresponding to the vehicle for which the specifications are calculated is deleted. (Step S12). This completes the process for calculating the vehicle specifications.
- feature measurement feature points are extracted for each surface of the vehicle, and each feature measurement is performed by performing motion stereo processing on the feature measurement feature points.
- the three-dimensional coordinates of the feature points for use are calculated.
- the vehicle specifications width, length, height
- the specification measurement is performed by robust image processing.
- Feature points can be detected.
- the vehicle specifications for example, width, length, height
- the vehicle specifications can be calculated by robust image processing.
- the present invention is not limited to the above embodiment. It will be apparent to those skilled in the art that the present invention may be practiced with various modifications. For example, in the above description, an embodiment in which all of the width, length, and height of the vehicle are calculated is described. However, all of the width, length, and height of the vehicle need not be calculated. The present invention is applicable when calculating at least one of the width, length, and height of a vehicle. In this case, only necessary ones of feature measurement feature points # 1 to # 6 may be detected.
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Abstract
An image processing device detects, with respect to a frame image, feature points (#1, #2) for specifications measurement which are feature points on side surfaces of a vehicle, and a feature point (#3) for specifications measurement which is a feature point on a lower surface, and calculates the width of the vehicle by performing a motion stereo process on the feature points (#1, #2, #3) for specifications measurement. The feature points (#1 to #3) for specifications measurement detected by the image processing device are detected such that the positions of the points have a degree of freedom on the side surfaces or the lower surface of the vehicle.
Description
本発明は、車両諸元計測処理装置、車両諸元計測方法及び記録媒体に関し、特に、車両諸元計測処理装置、車両諸元計測方法及び記録媒体に関し、特に、車両の諸元(幅、長さ、高さ)を計測するための装置及び方法に関する。
The present invention relates to a vehicle specification measurement processing device, a vehicle specification measurement method, and a recording medium, and more particularly, to a vehicle specification measurement processing device, a vehicle specification measurement method, and a recording medium, and more particularly to a vehicle specification (width, length). The present invention relates to an apparatus and a method for measuring the height.
高速道路、有料道路等の料金所には、通過する車両の車種を判別するための車種判別装置が設けられることがある。車種判別には様々な手法が用いられるが、近年では、車両の画像を撮影し、撮影した画像を用いて車種判別を行うことが検討されている。車両の画像からは車両に関する様々な情報を得ることができるため、車両の画像を用いた車種判別は、車種の判別の精度を高めるために有用である。
Tollgates such as expressways and toll roads may be provided with a vehicle type discriminating device for discriminating the type of vehicle passing through. Various methods are used for vehicle type discrimination. In recent years, it has been studied to take an image of a vehicle and perform vehicle type discrimination using the taken image. Since various information about the vehicle can be obtained from the vehicle image, the vehicle type determination using the vehicle image is useful for increasing the accuracy of the vehicle type determination.
車両の画像を用いた車種判別においては、車両の画像から特徴点を抽出し、抽出された特徴点に基づいて車種の判別を行うことがある。例えば、非特許文献1(J Prokai, G Medioni, "3-D model based vehicle recognition," Applications of Computer Vision (WACV), 2009)は、CG(computer graphic)によって車両の車種ごとに特徴点を学習することで作成したテンプレートを登録したデータベースを事前に用意し、画像から抽出した特徴点と、データベースのテンプレートとのマッチング処理によって車種を推定する技術を開示している。しかしながら、この方法では、車両の車種毎にテンプレートを用意することが必要になる。
In vehicle type determination using a vehicle image, a feature point may be extracted from the vehicle image, and the vehicle type may be determined based on the extracted feature point. For example, Non-Patent Document 1 (J Prokai, G Medoni, “3-D model based vehicle recognition,” Applications of Computer Vision (WACV), 2009) learns feature points for each vehicle model by CG (computer graphic). Thus, a technique is disclosed in which a database in which a template created is registered in advance is prepared, and a vehicle type is estimated by matching processing between a feature point extracted from an image and a database template. However, in this method, it is necessary to prepare a template for each vehicle type.
車両の画像を用いた車種判別の他の手法として、車両の諸元(例えば、幅、長さ、高さ)を画像処理によって算出し、算出された車両の諸元を車種判別のための情報として用いる技術が知られている。例えば、特許文献1(特開平11-86185号公報)は、撮影した車両の画像に対して補正を行うことで車両の正面及び側面の幾何補正画像を生成し、正面及び側面の幾何補正画像から車両の大きさを推定する技術を開示している。より具体的には、特許文献1に開示された技術では、タイヤと路面の接地位置が検出され、該接地位置と撮影装置の設置条件から車両の3次元空間での位置と進入角度が計算される。計算した車両の3次元空間での位置と進入角度に基づいて車両を撮影した画像に対して補正を行うことで車両の正面及び側面の幾何補正画像が生成され、生成された幾何補正画像から車両の大きさが推定される。
As another method of discriminating the vehicle type using the image of the vehicle, the vehicle specifications (for example, width, length, height) are calculated by image processing, and the calculated vehicle specification is information for discriminating the vehicle type. The technique used as is known. For example, Patent Document 1 (Japanese Patent Application Laid-Open No. 11-86185) generates a geometrically corrected image of the front and side surfaces of a vehicle by performing correction on the captured vehicle image, and generates the geometrically corrected images of the front and side surfaces. A technique for estimating the size of a vehicle is disclosed. More specifically, in the technique disclosed in Patent Document 1, the contact position between the tire and the road surface is detected, and the position and the approach angle in the three-dimensional space of the vehicle are calculated from the contact position and the installation conditions of the photographing device. The By correcting the image obtained by photographing the vehicle based on the calculated position and approach angle of the vehicle in the three-dimensional space, a geometric correction image of the front and side of the vehicle is generated, and the vehicle is generated from the generated geometric correction image. Is estimated.
また、非特許文献2(A. Lai, G. Fung and N. Yung, "Vehicle type classification from visual-based dimension estimation" IEEE, Intelligent Transportation Systems, pages 201-206, 2001)は、画像における車両の見かけの大きさから車両の諸元を推定する技術を開示している。具体的には、非特許文献2に開示された技術では、画像のうち、車両の外形に対応する領域が六角形の領域として抽出される。その六角形の頂点のうち、路面近傍の位置にある3つの頂点の座標が算出され、その座標から車両の幅、長さが算出され、更に、車両の高さが、実空間で高さ方向に対応する該六角形の辺の長さから算出される。
Non-Patent Document 2 (A. Lai, G. Fung and N. Yung, “Vehicle type classification from visual-based dimension estimation” IEEE, Intelligent Transportation Systems, pages 201-206, 2001) is the appearance of the vehicle in the image. Discloses a technique for estimating the specifications of a vehicle from the size of the vehicle. Specifically, in the technique disclosed in Non-Patent Document 2, a region corresponding to the outer shape of the vehicle is extracted as a hexagonal region from the image. Among the hexagonal vertices, the coordinates of the three vertices near the road surface are calculated, the vehicle width and length are calculated from the coordinates, and the vehicle height is the height direction in real space. Is calculated from the length of the side of the hexagon corresponding to.
車両の諸元を画像処理によって算出する手法においては、特徴点の抽出の確実性が求められないような画像処理、即ち、特徴点の検出についてロバストな画像処理で車両の諸元が算出可能であることが望ましい。特定の特徴点が算出できない場合に、車両の諸元が算出できない、又は、精度が低下するような手法は好ましくない。例えば、非特許文献2に開示された技術では、車両の外形に対応する六角形の頂点のうち路面近傍に対応する3つの頂点が特徴点として検知できなければ、車両の諸元を算出することができない。検出される特徴点の制約が強いことは、車両の諸元の画像処理による計測を不確実にしてしまう。
In the method of calculating vehicle specifications by image processing, it is possible to calculate vehicle specifications by image processing that does not require certainty of feature point extraction, that is, robust image processing for feature point detection. It is desirable to be. A method in which the vehicle specifications cannot be calculated or the accuracy decreases when a specific feature point cannot be calculated is not preferable. For example, in the technique disclosed in Non-Patent Document 2, if three vertices corresponding to the vicinity of the road surface among hexagonal vertices corresponding to the outer shape of the vehicle cannot be detected as feature points, the vehicle specifications are calculated. I can't. The strong restriction on the detected feature points makes measurement by image processing of vehicle specifications uncertain.
このような背景から、特徴点の検出についてロバストな画像処理によって車両の諸元(例えば、幅、長さ、高さ)を算出することができる技術の提供が求められている。
From such a background, there is a need to provide a technique capable of calculating vehicle specifications (for example, width, length, height) by robust image processing for feature point detection.
したがって、本発明の目的は、特徴点の検出についてロバストな画像処理によって車両の諸元(例えば、幅、長さ、高さ)を算出することができる技術を提供することにある。
Therefore, an object of the present invention is to provide a technique capable of calculating vehicle specifications (for example, width, length, height) by robust image processing for feature point detection.
本発明の一の観点では、車両諸元計測装置が、車両を逐次に撮影して車両のフレーム画像を取得する撮影装置と、フレーム画像に基づいて車両の幅を算出する画像処理装置とを具備している。画像処理装置は、フレーム画像のうちの少なくとも一について、車両の形状を近似する直方体の第1面にある特徴点である第1諸元計測用特徴点と、直方体の第2面にある特徴点である第2諸元計測用特徴点と、直方体の第3面にある特徴点である第3諸元計測用特徴点とを検出する特徴点検出手段と、第1諸元計測用特徴点、第2諸元計測用特徴点及び第3諸元計測用特徴点に基づいて車両の幅を算出する車両諸元算出手段とを備えている。ここで、第1面は、車両の第1側面に対応する直方体の面であり、第2面は、車両の第2側面に対応する直方体の面であり、第3面は、車両の下面に対応する直方体の面である。車両諸元算出手段は、第3諸元計測用特徴点の移動量から車両の移動量を算出し、車両の移動量を用いて第1諸元計測用特徴点及び第2諸元計測用特徴点に対してモーションステレオ処理を行うことによって第1諸元計測用特徴点及び第2諸元計測用特徴点の3次元座標を算出し、算出された第1諸元計測用特徴点及び第2諸元計測用特徴点の3次元座標から車両の幅を算出する。特徴点検出手段によって検出される第1諸元計測用特徴点の位置は、第1面の面内において自由度があり、特徴点検出手段によって検出される第2諸元計測用特徴点の位置は、第2面の面内において自由度がある。更に、特徴点検出手段によって検出される第3諸元計測用特徴点の位置は、第3面の面内において自由度がある。
In one aspect of the present invention, a vehicle specification measuring device includes an imaging device that sequentially captures a vehicle to obtain a frame image of the vehicle, and an image processing device that calculates the width of the vehicle based on the frame image. is doing. The image processing apparatus includes, for at least one of the frame images, a first feature measurement feature point that is a feature point on the first surface of a rectangular parallelepiped that approximates the shape of the vehicle, and a feature point that is on the second surface of the rectangular parallelepiped. Feature point detecting means for detecting the second feature measurement feature point and the third feature measurement feature point that is the feature point on the third surface of the rectangular parallelepiped, and the first feature measurement feature point, Vehicle feature calculation means for calculating the width of the vehicle based on the second feature measurement feature point and the third feature measurement feature point. Here, the first surface is a rectangular parallelepiped surface corresponding to the first side surface of the vehicle, the second surface is a rectangular parallelepiped surface corresponding to the second side surface of the vehicle, and the third surface is the lower surface of the vehicle. The corresponding rectangular parallelepiped surface. The vehicle specification calculation means calculates the movement amount of the vehicle from the movement amount of the third feature measurement feature point, and uses the vehicle movement amount to determine the first feature measurement feature point and the second feature measurement feature. 3D coordinates of the first feature measurement feature point and the second feature measurement feature point are calculated by performing motion stereo processing on the point, and the calculated first feature measurement feature point and second The vehicle width is calculated from the three-dimensional coordinates of the feature measurement feature points. The position of the first feature measurement feature point detected by the feature point detection means has a degree of freedom in the plane of the first surface, and the position of the second feature measurement feature point detected by the feature point detection means. Has a degree of freedom in the plane of the second surface. Furthermore, the position of the third feature measurement feature point detected by the feature point detection means has a degree of freedom in the plane of the third surface.
一実施形態では、特徴点検出手段が、フレーム画像から車両に対応する移動領域を抽出し、移動領域について、実空間において車両に接する線に対応しているフレーム画像内の線である接線を抽出し、抽出された接線の交点のうち第1面にある交点を第1諸元計測用特徴点として決定するように構成されてもよい。このとき、特徴点検出手段が、抽出された接線の交点のうち第2面にある交点を第2諸元計測用特徴点として決定するように構成されてもよく、抽出された接線の交点のうち第3面にある交点を第3諸元計測用特徴点として決定するように構成されてもよい。
In one embodiment, the feature point detection unit extracts a moving area corresponding to the vehicle from the frame image, and extracts a tangent line that is a line in the frame image corresponding to the line that contacts the vehicle in the real space. Then, the intersection point on the first surface among the intersection points of the extracted tangent lines may be determined as the first feature measurement feature point. At this time, the feature point detection means may be configured to determine an intersection point on the second surface among the intersection points of the extracted tangent lines as the second feature measurement feature point. Of these, the intersection point on the third surface may be determined as the third feature measurement feature point.
一実施形態では、特徴点検出手段が、フレーム画像から車両に対応する移動領域を抽出し、移動領域について、実空間において車両に接する線に対応しているフレーム画像内の線である接線を抽出し、抽出された接線のうち第1面にある部分で構成された第1探索路に沿って特徴点を探索することにより第1諸元計測用特徴点を決定するように構成されてもよい。このとき、特徴点検出手段が、抽出された接線のうち第2面にある部分で構成された第2探索路に沿って特徴点を探索することにより第2諸元計測用特徴点を決定するように構成されてもよく、特徴点検出手段が、抽出された接線のうち第3面にある部分で構成された第3探索路に沿って特徴点を探索することにより第3諸元計測用特徴点を決定するように構成されてもよい。
In one embodiment, the feature point detection unit extracts a moving area corresponding to the vehicle from the frame image, and extracts a tangent line that is a line in the frame image corresponding to the line that contacts the vehicle in the real space. The feature point for measuring the first item may be determined by searching for the feature point along the first search path constituted by the portion on the first surface of the extracted tangent line. . At this time, the feature point detecting means determines the second feature measurement feature point by searching for the feature point along the second search path constituted by the portion on the second surface of the extracted tangent line. The feature point detecting means may be configured to measure the third feature by searching for a feature point along a third search path constituted by a portion on the third surface of the extracted tangent line. It may be configured to determine feature points.
一実施形態では、特徴点検出手段が、車両の第1側面に存在すると想定される部品の第1テンプレートと第1テンプレートにおける特徴点の位置を示す第1特徴点位置データとを含む第1テンプレートデータベースを有していてもよい。この場合、特徴点検出手段は、フレーム画像に対し第1テンプレートデータベースのテンプレートとのテンプレートマッチングにより最もマッチする第1テンプレートの位置である第1マッチング位置を求め、第1マッチング位置と第1特徴点位置データとから決定した位置に第1諸元計測用特徴点があるとして第1諸元計測用特徴点を検出するように構成されてもよい。
In one embodiment, the feature point detection means includes a first template of a component assumed to exist on the first side surface of the vehicle, and first feature point position data indicating the position of the feature point in the first template. You may have a database. In this case, the feature point detecting means obtains a first matching position that is a position of the first template that most closely matches the frame image by template matching with the template of the first template database, and the first matching position and the first feature point are obtained. The first feature measurement feature point may be detected as the first feature measurement feature point at the position determined from the position data.
また、特徴点検出手段は、車両の第2側面に存在すると想定される部品の第2テンプレートと第2テンプレートにおける特徴点の位置を示す第2特徴点位置データとを含む第2テンプレートデータベースを有していてもよい。この場合、特徴点検出手段は、フレーム画像に対し第2テンプレートデータベースの第2テンプレートとのテンプレートマッチングにより最もマッチする第2テンプレートの位置である第2マッチング位置を求め、第2マッチング位置と第2特徴点位置データとから決定した位置に第2諸元計測用特徴点があるとして第2諸元計測用特徴点を検出するように構成されてもよい。
The feature point detecting means has a second template database including a second template of a part assumed to exist on the second side surface of the vehicle and second feature point position data indicating the position of the feature point in the second template. You may do it. In this case, the feature point detection means obtains a second matching position that is the position of the second template that most closely matches the frame image by template matching with the second template of the second template database, and determines the second matching position and the second matching position. The second feature measurement feature point may be detected on the assumption that the feature feature for second feature measurement exists at the position determined from the feature point position data.
更に、特徴点検出手段は、車両の下面に存在すると想定される部品の第3テンプレートと第3テンプレートにおける特徴点の位置を示す第3特徴点位置データとを含む第3テンプレートデータベースを有していてもよい。この場合、特徴点検出手段は、フレーム画像に対し第3テンプレートデータベースの第3テンプレートとのテンプレートマッチングにより最もマッチする第3テンプレートの位置である第3マッチング位置を求め、第3マッチング位置と第3特徴点位置データとから決定した位置に第3諸元計測用特徴点があるとして第3諸元計測用特徴点を検出するように構成されてもよい。
Further, the feature point detection means has a third template database including a third template of parts assumed to be present on the lower surface of the vehicle and third feature point position data indicating the position of the feature point in the third template. May be. In this case, the feature point detection means obtains a third matching position that is the position of the third template that most closely matches the frame image by template matching with the third template of the third template database, and determines the third matching position and the third matching position. The third feature measurement feature point may be detected by assuming that there is a feature feature for third feature measurement at a position determined from the feature point position data.
本発明の他の観点において、車両諸元計測装置が、車両を逐次に撮影して車両のフレーム画像を取得する撮影装置と、フレーム画像に基づいて車両の長さを算出する画像処理装置とを具備している。画像処理装置は、フレーム画像のうちの少なくとも一について、車両の形状を近似する直方体の第3面にある特徴点である第3諸元計測用特徴点と、直方体の第4面にある特徴点である第4諸元計測用特徴点と、直方体の第5面にある特徴点である第5諸元計測用特徴点とを検出する特徴点検出手段と、第3諸元計測用特徴点、第4諸元計測用特徴点及び第5諸元計測用特徴点に基づいて車両の長さを算出する車両諸元算出手段とを備えている。ここで、第3面は、車両の下面に対応する直方体の面であり、第4面は、車両の前面に対応する直方体の面であり、第5面は、車両の後面に対応する直方体の面である。車両諸元算出手段は、第3諸元計測用特徴点の移動量から車両の移動量を算出し、車両の移動量を用いて第4諸元計測用特徴点及び第5諸元計測用特徴点に対してモーションステレオ処理を行うことによって第4諸元計測用特徴点及び第5諸元計測用特徴点の3次元座標を算出し、算出された第4諸元計測用特徴点及び第5諸元計測用特徴点の3次元座標から車両の長さを算出する。特徴点検出手段によって検出される第3諸元計測用特徴点の位置は、第3面の面内において自由度がある。特徴点検出手段によって検出される第4諸元計測用特徴点の位置は、第4面の面内において自由度があり、特徴点検出手段によって検出される第5諸元計測用特徴点の位置は、第5面の面内において自由度がある。
In another aspect of the present invention, a vehicle specification measuring device includes a photographing device that sequentially photographs a vehicle to obtain a frame image of the vehicle, and an image processing device that calculates the length of the vehicle based on the frame image. It has. The image processing apparatus has a third feature measurement feature point that is a feature point on the third surface of a rectangular parallelepiped that approximates the shape of the vehicle and a feature point on the fourth surface of the rectangular parallelepiped for at least one of the frame images. Feature point detecting means for detecting the fourth feature measurement feature point and the fifth feature measurement feature point which is the feature point on the fifth surface of the rectangular parallelepiped, and the third feature measurement feature point, Vehicle feature calculation means for calculating the length of the vehicle based on the fourth feature measurement feature point and the fifth feature measurement feature point. Here, the third surface is a cuboid surface corresponding to the lower surface of the vehicle, the fourth surface is a cuboid surface corresponding to the front surface of the vehicle, and the fifth surface is a cuboid surface corresponding to the rear surface of the vehicle. Surface. The vehicle specification calculation means calculates the vehicle movement amount from the movement amount of the third feature measurement feature point, and uses the vehicle movement amount to calculate the fourth feature measurement feature point and the fifth feature measurement feature. By performing motion stereo processing on the point, the three-dimensional coordinates of the fourth feature measurement feature point and the fifth feature measurement feature point are calculated, and the calculated fourth feature measurement feature point and fifth feature point are calculated. The length of the vehicle is calculated from the three-dimensional coordinates of the feature measurement feature points. The position of the third feature measurement feature point detected by the feature point detection means has a degree of freedom within the third plane. The position of the fourth feature measurement feature point detected by the feature point detection means has a degree of freedom in the plane of the fourth surface, and the position of the fifth feature measurement feature point detected by the feature point detection means. Has a degree of freedom in the plane of the fifth surface.
本発明の更に他の観点において、車両諸元計測装置が、車両を逐次に撮影して車両のフレーム画像を取得する撮影装置と、フレーム画像に基づいて車両の高さを算出する画像処理装置とを具備する。画像処理装置は、フレーム画像のうちの少なくとも一について、車両の形状を近似する直方体の第3面にある特徴点である第3諸元計測用特徴点と、直方体の第6面にある特徴点である第6諸元計測用特徴点とを検出する特徴点検出手段と、第3諸元計測用特徴点及び第6諸元計測用特徴点に基づいて車両の高さを算出する車両諸元算出手段とを備えている。ここで、第3面は、車両の下面に対応する直方体の面であり、第6面は、車両の上面に対応する直方体の面である。車両諸元算出手段は、第3諸元計測用特徴点の移動量から車両の移動量を算出し、車両の移動量を用いて第3諸元計測用特徴点及び第6諸元計測用特徴点に対してモーションステレオ処理を行うことによって第3諸元計測用特徴点及び第6諸元計測用特徴点の3次元座標を算出し、算出された第3諸元計測用特徴点及び第6諸元計測用特徴点の3次元座標から車両の高さを算出する。特徴点検出手段によって検出される第3諸元計測用特徴点の位置は、第3面の面内において自由度があり、特徴点検出手段によって検出される第6諸元計測用特徴点の位置は、第6面の面内において自由度がある。
In still another aspect of the present invention, a vehicle specification measuring device captures a vehicle sequentially and acquires a frame image of the vehicle, and an image processing device calculates the height of the vehicle based on the frame image. It comprises. The image processing apparatus includes a third feature measurement feature point that is a feature point on a third surface of a rectangular parallelepiped approximating the shape of the vehicle and a feature point on a sixth surface of the rectangular parallelepiped for at least one of the frame images. Feature point detecting means for detecting the sixth feature measurement feature point, and the vehicle feature for calculating the height of the vehicle based on the third feature measurement feature point and the sixth feature measurement feature point. And a calculating means. Here, the third surface is a rectangular parallelepiped surface corresponding to the lower surface of the vehicle, and the sixth surface is a rectangular parallelepiped surface corresponding to the upper surface of the vehicle. The vehicle specification calculation means calculates the vehicle movement amount from the movement amount of the third feature measurement feature point, and uses the vehicle movement amount to calculate the third feature measurement feature point and the sixth feature measurement feature. By performing motion stereo processing on the point, three-dimensional coordinates of the third feature measurement feature point and the sixth feature measurement feature point are calculated, and the calculated third feature measurement feature point and sixth feature point are calculated. The vehicle height is calculated from the three-dimensional coordinates of the feature measurement feature points. The position of the third feature measurement feature point detected by the feature point detection means has a degree of freedom in the plane of the third surface, and the position of the sixth feature measurement feature point detected by the feature point detection means. Has a degree of freedom in the plane of the sixth surface.
本発明の更に他の観点において、車両諸元計測方法が、
車両を逐次に撮影して車両のフレーム画像を取得するステップと、
フレーム画像について、車両の形状を近似する直方体の第1面にある特徴点である第1諸元計測用特徴点と、直方体の第2面にある特徴点である第2諸元計測用特徴点と、直方体の第3面にある特徴点である第3諸元計測用特徴点とを検出するステップと、
第1諸元計測用特徴点、第2諸元計測用特徴点及び第3諸元計測用特徴点に基づいて車両の幅を算出するステップとを具備している。ここで、第1面は、車両の第1側面に対応する直方体の面であり、第2面は、車両の第2側面に対応する直方体の面であり、第3面は、車両の下面に対応する直方体の面である。車両の幅を算出するステップは、
第3諸元計測用特徴点の移動量から車両の移動量を算出するステップと、
車両の移動量を用いて第1諸元計測用特徴点及び第2諸元計測用特徴点に対してモーションステレオ処理を行うことによって第1諸元計測用特徴点及び第2諸元計測用特徴点の3次元座標を算出するステップと、
算出された第1諸元計測用特徴点及び第2諸元計測用特徴点の3次元座標から車両の幅を算出するステップとを含む。該検出するステップにおいて検出される第1諸元計測用特徴点の位置は、第1面の面内において自由度があり、該検出するステップにおいて検出される第2諸元計測用特徴点の位置は、第2面の面内において自由度がある。また、該検出するステップにおいて検出される第3諸元計測用特徴点の位置は、第3面の面内において自由度がある。 In still another aspect of the present invention, a vehicle specification measurement method includes:
Capturing the vehicle sequentially to obtain a frame image of the vehicle;
For a frame image, a first feature measurement feature point that is a feature point on the first surface of the rectangular parallelepiped approximating the shape of the vehicle, and a second feature measurement feature point that is a feature point on the second surface of the rectangular parallelepiped. Detecting a third feature measurement feature point that is a feature point on the third surface of the rectangular parallelepiped;
Calculating the width of the vehicle based on the first feature measurement feature point, the second feature measurement feature point, and the third feature measurement feature point. Here, the first surface is a rectangular parallelepiped surface corresponding to the first side surface of the vehicle, the second surface is a rectangular parallelepiped surface corresponding to the second side surface of the vehicle, and the third surface is the lower surface of the vehicle. The corresponding rectangular parallelepiped surface. The step of calculating the width of the vehicle is
Calculating a movement amount of the vehicle from a movement amount of the third feature measurement feature point;
A feature point for first specification measurement and a feature for second specification measurement are performed by performing motion stereo processing on the feature point for first specification measurement and the feature point for second specification measurement using the movement amount of the vehicle. Calculating the three-dimensional coordinates of the point;
Calculating the width of the vehicle from the calculated three-dimensional coordinates of the first feature measurement feature point and the second feature measurement feature point. The position of the first feature measurement feature point detected in the detection step has a degree of freedom in the plane of the first surface, and the position of the second feature measurement feature point detected in the detection step. Has a degree of freedom in the plane of the second surface. Further, the position of the third feature measurement feature point detected in the detecting step has a degree of freedom within the third surface.
車両を逐次に撮影して車両のフレーム画像を取得するステップと、
フレーム画像について、車両の形状を近似する直方体の第1面にある特徴点である第1諸元計測用特徴点と、直方体の第2面にある特徴点である第2諸元計測用特徴点と、直方体の第3面にある特徴点である第3諸元計測用特徴点とを検出するステップと、
第1諸元計測用特徴点、第2諸元計測用特徴点及び第3諸元計測用特徴点に基づいて車両の幅を算出するステップとを具備している。ここで、第1面は、車両の第1側面に対応する直方体の面であり、第2面は、車両の第2側面に対応する直方体の面であり、第3面は、車両の下面に対応する直方体の面である。車両の幅を算出するステップは、
第3諸元計測用特徴点の移動量から車両の移動量を算出するステップと、
車両の移動量を用いて第1諸元計測用特徴点及び第2諸元計測用特徴点に対してモーションステレオ処理を行うことによって第1諸元計測用特徴点及び第2諸元計測用特徴点の3次元座標を算出するステップと、
算出された第1諸元計測用特徴点及び第2諸元計測用特徴点の3次元座標から車両の幅を算出するステップとを含む。該検出するステップにおいて検出される第1諸元計測用特徴点の位置は、第1面の面内において自由度があり、該検出するステップにおいて検出される第2諸元計測用特徴点の位置は、第2面の面内において自由度がある。また、該検出するステップにおいて検出される第3諸元計測用特徴点の位置は、第3面の面内において自由度がある。 In still another aspect of the present invention, a vehicle specification measurement method includes:
Capturing the vehicle sequentially to obtain a frame image of the vehicle;
For a frame image, a first feature measurement feature point that is a feature point on the first surface of the rectangular parallelepiped approximating the shape of the vehicle, and a second feature measurement feature point that is a feature point on the second surface of the rectangular parallelepiped. Detecting a third feature measurement feature point that is a feature point on the third surface of the rectangular parallelepiped;
Calculating the width of the vehicle based on the first feature measurement feature point, the second feature measurement feature point, and the third feature measurement feature point. Here, the first surface is a rectangular parallelepiped surface corresponding to the first side surface of the vehicle, the second surface is a rectangular parallelepiped surface corresponding to the second side surface of the vehicle, and the third surface is the lower surface of the vehicle. The corresponding rectangular parallelepiped surface. The step of calculating the width of the vehicle is
Calculating a movement amount of the vehicle from a movement amount of the third feature measurement feature point;
A feature point for first specification measurement and a feature for second specification measurement are performed by performing motion stereo processing on the feature point for first specification measurement and the feature point for second specification measurement using the movement amount of the vehicle. Calculating the three-dimensional coordinates of the point;
Calculating the width of the vehicle from the calculated three-dimensional coordinates of the first feature measurement feature point and the second feature measurement feature point. The position of the first feature measurement feature point detected in the detection step has a degree of freedom in the plane of the first surface, and the position of the second feature measurement feature point detected in the detection step. Has a degree of freedom in the plane of the second surface. Further, the position of the third feature measurement feature point detected in the detecting step has a degree of freedom within the third surface.
本発明の更に他の観点では、車両諸元計測方法が、
車両を逐次に撮影して車両のフレーム画像を取得するステップと、
フレーム画像のうちの少なくとも一について、車両の形状を近似する直方体の第3面にある特徴点である第3諸元計測用特徴点と、直方体の第4面にある特徴点である第4諸元計測用特徴点と、直方体の第5面にある特徴点である第5諸元計測用特徴点とを検出するステップと、
第3諸元計測用特徴点、第4諸元計測用特徴点及び第5諸元計測用特徴点に基づいて車両の長さを算出するステップ
とを具備する。ここで、第3面は、車両の下面に対応する直方体の面であり、第4面は、車両の前面に対応する直方体の面であり、第5面は、車両の後面に対応する直方体の面である。車両の長さを算出するステップは、
第3諸元計測用特徴点の移動量から車両の移動量を算出するステップと、
車両の移動量を用いて第4諸元計測用特徴点及び第5諸元計測用特徴点に対してモーションステレオ処理を行うことによって第4諸元計測用特徴点及び第5諸元計測用特徴点の3次元座標を算出するステップと、
算出された第4諸元計測用特徴点及び第5諸元計測用特徴点の3次元座標から車両の長さを算出するステップとを含む。該検出するステップにおいて検出される第3諸元計測用特徴点の位置は、第3面の面内において自由度がある。また、該検出するステップにおいて検出される第4諸元計測用特徴点の位置は、第4面の面内において自由度があり、該検出するステップにおいて検出される第5諸元計測用特徴点の位置は、第5面の面内において自由度がある。 In still another aspect of the present invention, a vehicle specification measurement method includes:
Capturing the vehicle sequentially to obtain a frame image of the vehicle;
For at least one of the frame images, a third feature measurement feature point that is a feature point on the third surface of the cuboid that approximates the shape of the vehicle, and a fourth feature point that is a feature point on the fourth surface of the cuboid. Detecting an original measurement feature point and a fifth feature measurement feature point that is a feature point on the fifth surface of the rectangular parallelepiped;
Calculating the length of the vehicle based on the third feature measurement feature point, the fourth feature measurement feature point, and the fifth feature measurement feature point. Here, the third surface is a cuboid surface corresponding to the lower surface of the vehicle, the fourth surface is a cuboid surface corresponding to the front surface of the vehicle, and the fifth surface is a cuboid surface corresponding to the rear surface of the vehicle. Surface. The step of calculating the length of the vehicle is:
Calculating a movement amount of the vehicle from a movement amount of the third feature measurement feature point;
The fourth feature measurement feature point and the fifth feature measurement feature are obtained by performing motion stereo processing on the fourth feature measurement feature point and the fifth feature measurement feature point using the movement amount of the vehicle. Calculating the three-dimensional coordinates of the point;
Calculating the length of the vehicle from the calculated three-dimensional coordinates of the fourth feature measurement feature point and the fifth feature measurement feature point. The position of the third feature measurement feature point detected in the detecting step has a degree of freedom within the third surface. Further, the position of the fourth feature measurement feature point detected in the detection step has a degree of freedom in the plane of the fourth surface, and the fifth feature measurement feature point detected in the detection step. Has a degree of freedom in the plane of the fifth surface.
車両を逐次に撮影して車両のフレーム画像を取得するステップと、
フレーム画像のうちの少なくとも一について、車両の形状を近似する直方体の第3面にある特徴点である第3諸元計測用特徴点と、直方体の第4面にある特徴点である第4諸元計測用特徴点と、直方体の第5面にある特徴点である第5諸元計測用特徴点とを検出するステップと、
第3諸元計測用特徴点、第4諸元計測用特徴点及び第5諸元計測用特徴点に基づいて車両の長さを算出するステップ
とを具備する。ここで、第3面は、車両の下面に対応する直方体の面であり、第4面は、車両の前面に対応する直方体の面であり、第5面は、車両の後面に対応する直方体の面である。車両の長さを算出するステップは、
第3諸元計測用特徴点の移動量から車両の移動量を算出するステップと、
車両の移動量を用いて第4諸元計測用特徴点及び第5諸元計測用特徴点に対してモーションステレオ処理を行うことによって第4諸元計測用特徴点及び第5諸元計測用特徴点の3次元座標を算出するステップと、
算出された第4諸元計測用特徴点及び第5諸元計測用特徴点の3次元座標から車両の長さを算出するステップとを含む。該検出するステップにおいて検出される第3諸元計測用特徴点の位置は、第3面の面内において自由度がある。また、該検出するステップにおいて検出される第4諸元計測用特徴点の位置は、第4面の面内において自由度があり、該検出するステップにおいて検出される第5諸元計測用特徴点の位置は、第5面の面内において自由度がある。 In still another aspect of the present invention, a vehicle specification measurement method includes:
Capturing the vehicle sequentially to obtain a frame image of the vehicle;
For at least one of the frame images, a third feature measurement feature point that is a feature point on the third surface of the cuboid that approximates the shape of the vehicle, and a fourth feature point that is a feature point on the fourth surface of the cuboid. Detecting an original measurement feature point and a fifth feature measurement feature point that is a feature point on the fifth surface of the rectangular parallelepiped;
Calculating the length of the vehicle based on the third feature measurement feature point, the fourth feature measurement feature point, and the fifth feature measurement feature point. Here, the third surface is a cuboid surface corresponding to the lower surface of the vehicle, the fourth surface is a cuboid surface corresponding to the front surface of the vehicle, and the fifth surface is a cuboid surface corresponding to the rear surface of the vehicle. Surface. The step of calculating the length of the vehicle is:
Calculating a movement amount of the vehicle from a movement amount of the third feature measurement feature point;
The fourth feature measurement feature point and the fifth feature measurement feature are obtained by performing motion stereo processing on the fourth feature measurement feature point and the fifth feature measurement feature point using the movement amount of the vehicle. Calculating the three-dimensional coordinates of the point;
Calculating the length of the vehicle from the calculated three-dimensional coordinates of the fourth feature measurement feature point and the fifth feature measurement feature point. The position of the third feature measurement feature point detected in the detecting step has a degree of freedom within the third surface. Further, the position of the fourth feature measurement feature point detected in the detection step has a degree of freedom in the plane of the fourth surface, and the fifth feature measurement feature point detected in the detection step. Has a degree of freedom in the plane of the fifth surface.
本発明の更に他の観点では、車両諸元計測方法が、
車両を逐次に撮影して車両のフレーム画像を取得するステップと、
フレーム画像のうちの少なくとも一について、車両の形状を近似する直方体の第3面にある特徴点である第3諸元計測用特徴点と、直方体の第6面にある特徴点である第6諸元計測用特徴点とを検出するステップと、
第3諸元計測用特徴点及び第6諸元計測用特徴点に基づいて車両の高さを算出するステップ
とを具備する。ここで、第3面は、車両の下面に対応する直方体の面であり、第6面は、車両の上面に対応する直方体の面である。車両の高さを算出するステップは、
第3諸元計測用特徴点の移動量から車両の移動量を算出するステップと、
車両の移動量を用いて第3諸元計測用特徴点及び第6諸元計測用特徴点に対してモーションステレオ処理を行うことによって第3諸元計測用特徴点及び第6諸元計測用特徴点の3次元座標を算出するステップと、
算出された第3諸元計測用特徴点及び第6諸元計測用特徴点の3次元座標から車両の高さを算出するステップ
とを含む。検出するステップにおいて検出される第3諸元計測用特徴点の位置は、第3面の面内において自由度があり、検出するステップにおいて検出される第6諸元計測用特徴点の位置は、第6面の面内において自由度がある。 In still another aspect of the present invention, a vehicle specification measurement method includes:
Capturing the vehicle sequentially to obtain a frame image of the vehicle;
For at least one of the frame images, a third feature measurement feature point that is a feature point on the third surface of the cuboid that approximates the shape of the vehicle, and a sixth feature point that is the feature point on the sixth surface of the cuboid. Detecting original measurement feature points;
Calculating the height of the vehicle based on the third feature measurement feature point and the sixth feature measurement feature point. Here, the third surface is a rectangular parallelepiped surface corresponding to the lower surface of the vehicle, and the sixth surface is a rectangular parallelepiped surface corresponding to the upper surface of the vehicle. The step of calculating the height of the vehicle is
Calculating a movement amount of the vehicle from a movement amount of the third feature measurement feature point;
The third feature measurement feature point and the sixth feature measurement feature are obtained by performing motion stereo processing on the third feature measurement feature point and the sixth feature measurement feature point using the movement amount of the vehicle. Calculating the three-dimensional coordinates of the point;
Calculating the height of the vehicle from the calculated three-dimensional coordinate of the third feature measurement feature point and the sixth feature measurement feature point. The position of the third feature measurement feature point detected in the detection step has a degree of freedom in the plane of the third surface, and the position of the sixth feature measurement feature point detected in the detection step is There is a degree of freedom in the plane of the sixth plane.
車両を逐次に撮影して車両のフレーム画像を取得するステップと、
フレーム画像のうちの少なくとも一について、車両の形状を近似する直方体の第3面にある特徴点である第3諸元計測用特徴点と、直方体の第6面にある特徴点である第6諸元計測用特徴点とを検出するステップと、
第3諸元計測用特徴点及び第6諸元計測用特徴点に基づいて車両の高さを算出するステップ
とを具備する。ここで、第3面は、車両の下面に対応する直方体の面であり、第6面は、車両の上面に対応する直方体の面である。車両の高さを算出するステップは、
第3諸元計測用特徴点の移動量から車両の移動量を算出するステップと、
車両の移動量を用いて第3諸元計測用特徴点及び第6諸元計測用特徴点に対してモーションステレオ処理を行うことによって第3諸元計測用特徴点及び第6諸元計測用特徴点の3次元座標を算出するステップと、
算出された第3諸元計測用特徴点及び第6諸元計測用特徴点の3次元座標から車両の高さを算出するステップ
とを含む。検出するステップにおいて検出される第3諸元計測用特徴点の位置は、第3面の面内において自由度があり、検出するステップにおいて検出される第6諸元計測用特徴点の位置は、第6面の面内において自由度がある。 In still another aspect of the present invention, a vehicle specification measurement method includes:
Capturing the vehicle sequentially to obtain a frame image of the vehicle;
For at least one of the frame images, a third feature measurement feature point that is a feature point on the third surface of the cuboid that approximates the shape of the vehicle, and a sixth feature point that is the feature point on the sixth surface of the cuboid. Detecting original measurement feature points;
Calculating the height of the vehicle based on the third feature measurement feature point and the sixth feature measurement feature point. Here, the third surface is a rectangular parallelepiped surface corresponding to the lower surface of the vehicle, and the sixth surface is a rectangular parallelepiped surface corresponding to the upper surface of the vehicle. The step of calculating the height of the vehicle is
Calculating a movement amount of the vehicle from a movement amount of the third feature measurement feature point;
The third feature measurement feature point and the sixth feature measurement feature are obtained by performing motion stereo processing on the third feature measurement feature point and the sixth feature measurement feature point using the movement amount of the vehicle. Calculating the three-dimensional coordinates of the point;
Calculating the height of the vehicle from the calculated three-dimensional coordinate of the third feature measurement feature point and the sixth feature measurement feature point. The position of the third feature measurement feature point detected in the detection step has a degree of freedom in the plane of the third surface, and the position of the sixth feature measurement feature point detected in the detection step is There is a degree of freedom in the plane of the sixth plane.
上記の車両諸元計測方法は、演算装置がプログラムを実行することによって行われても良い。この場合、該プログラムは、該プログラムを記録した記録媒体を用いて演算装置にインストールされても良い。
The vehicle specification measurement method described above may be performed by the arithmetic device executing a program. In this case, the program may be installed in the arithmetic device using a recording medium on which the program is recorded.
本発明によれば、特徴点の検出についてロバストな画像処理によって車両の諸元(例えば、幅、長さ、高さ)を算出することができる技術を提供することができる。
According to the present invention, it is possible to provide a technique capable of calculating vehicle specifications (for example, width, length, height) by robust image processing for feature point detection.
まず、本発明の一実施形態の車両諸元計測方法の概略について説明する。本実施形態では、走行する車両の画像が逐次に撮影され(即ち、異なる時刻において車両の画像が撮像され)、該複数の画像について特徴点の検知と追尾が行われる。更に、特徴点についてモーションステレオ(motion stereo)処理が行われる。モーションステレオ処理とは、移動する物体について異なる時刻に画像を撮影すると共に、何らかの手法で該物体の移動距離を算出し(撮影された画像自体から算出してもよい)、撮影された画像と該物体の移動距離とから、物体と共に移動する3次元座標における物体の3次元座標を計算する技術である。同一場所から撮像された画像であっても物体の位置が該移動距離だけ異なるという情報から、一般的なステレオ処理と類似した手法により、物体の3次元座標が計算可能である。本発明では、モーションステレオ処理によって特徴点の3次元座標(厳密には、車両と共に移動する3次元座標における3次元座標)が計算され、その3次元座標から車両の諸元が算出される。
First, an outline of a vehicle specification measurement method according to an embodiment of the present invention will be described. In the present embodiment, images of a traveling vehicle are sequentially taken (that is, vehicle images are taken at different times), and feature points are detected and tracked for the plurality of images. Furthermore, motion stereo processing is performed on the feature points. Motion stereo processing is to capture an image of a moving object at different times, calculate the moving distance of the object by some method (may be calculated from the captured image itself), This is a technique for calculating the three-dimensional coordinates of an object in the three-dimensional coordinates that move with the object from the movement distance of the object. Even if the images are taken from the same place, the three-dimensional coordinates of the object can be calculated by a method similar to general stereo processing from the information that the position of the object differs by the movement distance. In the present invention, the three-dimensional coordinates of the feature points (strictly speaking, the three-dimensional coordinates in the three-dimensional coordinates moving with the vehicle) are calculated by motion stereo processing, and the specifications of the vehicle are calculated from the three-dimensional coordinates.
本実施形態における車両の諸元の計測処理の一つの特徴は、車両の幅、長さ、高さの算出に用いられる特徴点の抽出の手法にある。図1A~図1Cは、それぞれ、車両の幅、長さ、高さの計測に用いられる特徴点を示す図である。本発明では、車両の外形を近似する直方体30が定義され、該直方体30の特定面に沿った位置にある特徴点が、車両の幅、長さ、高さの計測に用いられる特徴点として使用される。なお、直方体30は、あくまで仮想的に決定されるものである。図1A~図1Cにおいて、記号v1~v8は、直方体30の頂点を表わしている。なお、車両の幅、長さ、高さの計測に用いられる特徴点を、(後述されるような、画像から移動体を検知するために使用される特徴点(移動体検出用特徴点)と区別するために)、以下では、諸元計測用特徴点と呼ぶことにする。
One feature of the measurement processing of the vehicle specifications in the present embodiment is a feature point extraction technique used for calculating the width, length, and height of the vehicle. 1A to 1C are diagrams showing feature points used for measuring the width, length, and height of a vehicle, respectively. In the present invention, a rectangular parallelepiped 30 that approximates the outer shape of the vehicle is defined, and the feature points at positions along a specific surface of the rectangular parallelepiped 30 are used as feature points used for measuring the width, length, and height of the vehicle. Is done. Note that the rectangular parallelepiped 30 is virtually determined. 1A to 1C, symbols v 1 to v 8 represent vertices of the rectangular parallelepiped 30. Note that the feature points used for measuring the width, length, and height of the vehicle are (feature points (feature points for moving object detection) used for detecting a moving object from an image, as will be described later). For the sake of distinction, hereinafter, it will be referred to as feature measurement feature points.
詳細には、図1Aに図示されているように、車両の幅の算出においては次の3種類の諸元計測用特徴点が使用される:
諸元計測用特徴点#1:車両の側面31にある特徴点(厳密には、車両の側面31に対応する直方体30の面に沿った位置にある特徴点)
諸元計測用特徴点#2:車両の側面32にある特徴点(厳密には、車両の側面32に対応する直方体30の面に沿った位置にある特徴点
諸元計測用特徴点#3:車両の下面33にある特徴点(厳密には、車両の下面33に対応する直方体30の面に沿った位置にある特徴点)
ここで、側面31は、車両の2つの側面のうち、走行する車両を計測するカメラに対向する方の側面であり、側面32は、他方の側面である。側面31に対応する直方体30の面は、頂点v1~v4を有しており、側面32に対応する直方体30の面は、頂点v5~v6を有している。 Specifically, as shown in FIG. 1A, the following three types of feature measurement feature points are used in calculating the vehicle width:
Feature measurement feature point # 1: feature point on theside surface 31 of the vehicle (strictly, a feature point at a position along the surface of the rectangular parallelepiped 30 corresponding to the side surface 31 of the vehicle)
Feature measurement feature point # 2: Feature point on theside surface 32 of the vehicle (strictly, feature point located along the surface of the rectangular parallelepiped 30 corresponding to the side surface 32 of the vehicle Feature measurement feature point # 3: A feature point on the lower surface 33 of the vehicle (strictly, a feature point at a position along the surface of the rectangular parallelepiped 30 corresponding to the lower surface 33 of the vehicle)
Here, theside surface 31 is the side surface of the two side surfaces of the vehicle that faces the camera that measures the traveling vehicle, and the side surface 32 is the other side surface. The surface of the cuboid 30 corresponding to the side surface 31 has vertices v 1 to v 4 , and the surface of the cuboid 30 corresponding to the side surface 32 has vertices v 5 to v 6 .
諸元計測用特徴点#1:車両の側面31にある特徴点(厳密には、車両の側面31に対応する直方体30の面に沿った位置にある特徴点)
諸元計測用特徴点#2:車両の側面32にある特徴点(厳密には、車両の側面32に対応する直方体30の面に沿った位置にある特徴点
諸元計測用特徴点#3:車両の下面33にある特徴点(厳密には、車両の下面33に対応する直方体30の面に沿った位置にある特徴点)
ここで、側面31は、車両の2つの側面のうち、走行する車両を計測するカメラに対向する方の側面であり、側面32は、他方の側面である。側面31に対応する直方体30の面は、頂点v1~v4を有しており、側面32に対応する直方体30の面は、頂点v5~v6を有している。 Specifically, as shown in FIG. 1A, the following three types of feature measurement feature points are used in calculating the vehicle width:
Feature measurement feature point # 1: feature point on the
Feature measurement feature point # 2: Feature point on the
Here, the
本実施形態では、諸元計測用特徴点#1、#2、#3は、それぞれ、側面31、32、下面33にあるという条件を満たしていれば、任意の位置から抽出することが許容される。例えば、カメラに対向する側面31については、側面31の任意の位置にある特徴点が、諸元計測用特徴点#1として使用されることが許容される。
In the present embodiment, the feature measurement feature points # 1, # 2, and # 3 are allowed to be extracted from arbitrary positions as long as the conditions that the feature points # 1, # 2, and # 3 are on the side surfaces 31, 32 and the lower surface 33 are satisfied. The For example, with respect to the side surface 31 facing the camera, the feature point at an arbitrary position of the side surface 31 is allowed to be used as the feature measurement feature point # 1.
同様に、カメラと反対側の側面32についても、側面32の任意の位置にある特徴点が、諸元計測用特徴点#2として使用されることが許容される。ただし、側面32は実際には車両に隠れているので、実際には、辺v5v6及び辺v6v7に沿った車両の輪郭の任意の位置から抽出された特徴点が、側面32の上の特徴点として使用されることになる。
Similarly, on the side surface 32 opposite to the camera, it is allowed that a feature point at an arbitrary position on the side surface 32 is used as a feature measurement feature point # 2. However, since the side surface 32 is actually hidden by the vehicle, in practice, feature points extracted from arbitrary positions of the contour of the vehicle along the sides v 5 v 6 and v 6 v 7 are the side surfaces 32. It will be used as a feature point above.
更に、下面33についても、下面33の任意の位置にある特徴点が、諸元計測用特徴点#3として使用されることが許容される。ただし、下面33は実際には車両に隠れているので、実際には、辺v3v7及び辺v3v4に沿った車両の輪郭の任意の位置から抽出された特徴点が、下面33の上の特徴点として使用されることになる。
Further, with respect to the lower surface 33, a feature point at an arbitrary position on the lower surface 33 is allowed to be used as the feature measurement feature point # 3. However, since the lower surface 33 is actually hidden by the vehicle, the feature points extracted from arbitrary positions of the contour of the vehicle along the sides v 3 v 7 and v 3 v 4 are actually lower surface 33. It will be used as a feature point above.
後述されるように、抽出された諸元計測用特徴点#1~#3のうち、下面33にある諸元計測用特徴点#3は、車両の移動距離を算出するために使用される。更に、算出された移動距離を用いて諸元計測用特徴点#1、#2についてモーションステレオ処理が行われ、車両とともに移動する3次元座標系における諸元計測用特徴点#1、#2の3次元座標(例えば、諸元計測用特徴点#3に対する相対座標)が算出され、算出された諸元計測用特徴点#1、#2の3次元座標から、車両の幅が算出される。
As will be described later, among the extracted feature measurement feature points # 1 to # 3, the feature measurement feature point # 3 on the lower surface 33 is used to calculate the moving distance of the vehicle. Furthermore, motion stereo processing is performed for the feature measurement feature points # 1 and # 2 using the calculated moving distance, and the feature measurement feature points # 1 and # 2 in the three-dimensional coordinate system moving with the vehicle. Three-dimensional coordinates (for example, relative coordinates with respect to the feature measurement feature point # 3) are calculated, and the width of the vehicle is calculated from the calculated three-dimensional coordinates of the feature measurement feature points # 1 and # 2.
一方、図1Bに図示されているように、車両の長さの算出においては、次の3種類の諸元計測用特徴点が使用される:
諸元計測用特徴点#3:車両の下面33にある特徴点
諸元計測用特徴点#4:車両の前面34にある特徴点(厳密には、車両の前面34に対応する直方体30の面に沿った位置にある特徴点)
諸元計測用特徴点#5:車両の後面35にある特徴点(厳密には、車両の後面35に対応する直方体30の面に沿った位置にある特徴点) On the other hand, as shown in FIG. 1B, the following three types of feature measurement feature points are used in calculating the vehicle length:
Feature measurement feature point # 3: Feature point on thelower surface 33 of the vehicle Feature measurement feature point # 4: Feature point on the front surface 34 of the vehicle (strictly, the surface of the rectangular parallelepiped 30 corresponding to the front surface 34 of the vehicle) Feature points located along
Feature measurement feature point # 5: feature point on therear surface 35 of the vehicle (strictly, a feature point at a position along the surface of the rectangular parallelepiped 30 corresponding to the rear surface 35 of the vehicle)
諸元計測用特徴点#3:車両の下面33にある特徴点
諸元計測用特徴点#4:車両の前面34にある特徴点(厳密には、車両の前面34に対応する直方体30の面に沿った位置にある特徴点)
諸元計測用特徴点#5:車両の後面35にある特徴点(厳密には、車両の後面35に対応する直方体30の面に沿った位置にある特徴点) On the other hand, as shown in FIG. 1B, the following three types of feature measurement feature points are used in calculating the vehicle length:
Feature measurement feature point # 3: Feature point on the
Feature measurement feature point # 5: feature point on the
諸元計測用特徴点#4、#5も、諸元計測用特徴点#1~#3と同様に、前面34、後面35にあるという条件を満たしていれば、任意の位置から抽出することが許容される。ただし、実際に抽出される特徴点の位置は、カメラの配置によって異なる。カメラが、走行する車両を後ろから撮影するように配置されている場合、後面35がカメラに対向することになる。この場合、後面35については、後面35の任意の位置にある特徴点が、諸元計測用特徴点#5として使用されることが許容される一方で、実際には車両に隠れている前面34については、辺v1v5及び辺v1v4に沿った車両の輪郭の任意の位置から抽出された特徴点が、前面34の上の諸元計測用特徴点#4として使用されることになる。図1Bには、このようなカメラの配置の場合が図示されている。一方、カメラが、走行する車両を前から撮影するように配置されている場合、前面34がカメラに対向することになる。この場合、前面34については、前面34の任意の位置にある特徴点が、諸元計測用特徴点#4として使用されることが許容される一方で、実際には車両に隠れている後面35については、カメラから撮影可能な辺に沿った車両の輪郭の任意の位置から抽出された特徴点が、後面35の上の諸元計測用特徴点#5として使用されることになる。
The feature measurement feature points # 4 and # 5 are extracted from arbitrary positions as long as the condition that the feature measurement feature points # 4 and # 5 are on the front surface 34 and the rear surface 35 is satisfied as in the feature measurement feature points # 1 to # 3. Is acceptable. However, the positions of the feature points that are actually extracted differ depending on the arrangement of the cameras. When the camera is arranged so as to photograph the traveling vehicle from behind, the rear surface 35 faces the camera. In this case, for the rear surface 35, the feature point at an arbitrary position on the rear surface 35 is allowed to be used as the feature measurement feature point # 5, while the front surface 34 that is actually hidden in the vehicle. , Feature points extracted from arbitrary positions of the vehicle contour along the sides v 1 v 5 and v 1 v 4 are used as feature measurement feature points # 4 on the front surface 34. become. FIG. 1B shows such a camera arrangement. On the other hand, when the camera is arranged so as to photograph the traveling vehicle from the front, the front surface 34 faces the camera. In this case, with respect to the front surface 34, a feature point at an arbitrary position on the front surface 34 is allowed to be used as a feature measurement feature point # 4, while the rear surface 35 that is actually hidden in the vehicle. For feature points, feature points extracted from an arbitrary position on the contour of the vehicle along the side that can be photographed from the camera will be used as feature measurement feature points # 5 on the rear surface 35.
車両の長さの算出においては、下面33にある諸元計測用特徴点#3に基づいて算出された車両の移動距離を用いて諸元計測用特徴点#4、#5についてモーションステレオ処理が行われる。これにより、車両とともに移動する3次元座標系における諸元計測用特徴点#4、#5の3次元座標(例えば、諸元計測用特徴点#3に対する相対座標)が算出される、算出された諸元計測用特徴点#4、#5の3次元座標から、車両の長さが算出される。
In calculating the length of the vehicle, motion stereo processing is performed on the feature measurement feature points # 4 and # 5 using the travel distance of the vehicle calculated based on the feature measurement feature point # 3 on the lower surface 33. Done. Thereby, the three-dimensional coordinates of the feature measurement feature points # 4 and # 5 in the three-dimensional coordinate system moving with the vehicle (for example, the relative coordinates with respect to the feature measurement feature point # 3) are calculated. The length of the vehicle is calculated from the three-dimensional coordinates of the feature measurement feature points # 4 and # 5.
更に、図1Cに図示されているように、車両の高さの算出においては次の2種類の諸元計測用特徴点が使用される:
諸元計測用特徴点#3:車両の下面33にある特徴点(厳密には、車両の下面33に対応する直方体30の面に沿った位置にある特徴点)
諸元計測用特徴点#6:車両の上面36にある特徴点(厳密には、車両の上面36に対応する直方体30の面に沿った位置にある特徴点) Further, as shown in FIG. 1C, the following two types of feature measurement feature points are used in calculating the height of the vehicle:
Feature measurement feature point # 3: feature point on thelower surface 33 of the vehicle (strictly, a feature point at a position along the surface of the rectangular parallelepiped 30 corresponding to the lower surface 33 of the vehicle)
Feature measurement feature point # 6: feature point on theupper surface 36 of the vehicle (strictly, a feature point at a position along the surface of the rectangular parallelepiped 30 corresponding to the upper surface 36 of the vehicle)
諸元計測用特徴点#3:車両の下面33にある特徴点(厳密には、車両の下面33に対応する直方体30の面に沿った位置にある特徴点)
諸元計測用特徴点#6:車両の上面36にある特徴点(厳密には、車両の上面36に対応する直方体30の面に沿った位置にある特徴点) Further, as shown in FIG. 1C, the following two types of feature measurement feature points are used in calculating the height of the vehicle:
Feature measurement feature point # 3: feature point on the
Feature measurement feature point # 6: feature point on the
諸元計測用特徴点#1~#5と同様に、諸元計測用特徴点#6も、上面36にあるという条件を満たしていれば、任意の位置から抽出することが許容される。道路を走行する車両を撮影する場合、通常、カメラは車両の上方に設置される(例えば、道路に設けられたガントリに設置される)ので、車両の上面36は、通常、その全体が撮影されることに留意されたい。
Similarly to the feature measurement feature points # 1 to # 5, the feature measurement feature point # 6 is allowed to be extracted from an arbitrary position as long as it satisfies the condition of being on the upper surface. When photographing a vehicle traveling on a road, the camera is usually installed above the vehicle (for example, installed in a gantry provided on the road), so that the entire upper surface 36 of the vehicle is usually photographed. Please note that.
車両の高さの算出においては、下面33にある諸元計測用特徴点#3に基づいて算出された車両の移動距離を用いて諸元計測用特徴点#6についてモーションステレオ処理が行われる。これにより、車両とともに移動する3次元座標系における諸元計測用特徴点#3、#6の3次元座標(例えば、諸元計測用特徴点#3に対する相対座標)が算出され、算出された諸元計測用特徴点#3、#6の3次元座標から、車両の高さが算出される。
In calculating the height of the vehicle, motion stereo processing is performed on the feature measurement feature point # 6 using the vehicle movement distance calculated based on the feature measurement feature point # 3 on the lower surface 33. As a result, the three-dimensional coordinates of the feature measurement feature points # 3 and # 6 in the three-dimensional coordinate system moving with the vehicle (for example, relative coordinates with respect to the feature measurement feature point # 3) are calculated, and the calculated specifications are calculated. The height of the vehicle is calculated from the three-dimensional coordinates of the original measurement feature points # 3 and # 6.
続いて、本発明の一実施形態における車両諸元計測処理装置及び車両諸元計測方法について、詳細に説明する。
Subsequently, a vehicle specification measurement processing device and a vehicle specification measurement method according to an embodiment of the present invention will be described in detail.
図2は、本実施形態の車両諸元計測処理装置10の構成の例を示すブロック図である。車両諸元計測処理装置10は、カメラ1と、画像処理装置2とを備えている。カメラ1は、道路を走行する車両を撮影する撮像装置である。カメラ1は、車両の画像(フレーム画像)の画像データ21を生成し、生成した画像データ21を画像処理装置2に供給する。画像処理装置2は、カメラ1から受け取った画像データ21に対して画像処理を行って画像データ21の画像に撮影されている車両の諸元、より具体的には、車両の幅、長さ、高さを計測し、車両の幅、長さ、高さを示す車両諸元データ22を生成する。
FIG. 2 is a block diagram showing an example of the configuration of the vehicle specification measurement processing apparatus 10 of the present embodiment. The vehicle specification measurement processing device 10 includes a camera 1 and an image processing device 2. The camera 1 is an imaging device that captures a vehicle traveling on a road. The camera 1 generates image data 21 of a vehicle image (frame image) and supplies the generated image data 21 to the image processing device 2. The image processing device 2 performs image processing on the image data 21 received from the camera 1 and the specifications of the vehicle captured in the image of the image data 21, more specifically, the width, length of the vehicle, The height is measured, and vehicle specification data 22 indicating the width, length, and height of the vehicle is generated.
画像処理装置2は、画像処理IC(integrated circuit)3と、外部インターフェース4と、外部記憶装置5と、メモリ6と、ROM(read only memory)7とを備えている。外部インターフェース4は、カメラ1に接続されており、カメラ1から受け取った画像データ21を、画像処理IC3に供給する。外部記憶装置5は、画像処理装置2における画像処理において生成されるデータを保存する。外部記憶装置5に保存されるデータは、車両諸元データ22を含んでいる。メモリ6は、画像処理IC3による演算処理のワーキングエリアとして使用される。ROM7は、画像処理IC3によって実行されるプログラムを保存している。ROM7に記憶されているプログラムは、車両の諸元を計測する画像処理を実行するためのプログラムである車両諸元計測処理プログラム7aを含んでいる。
The image processing apparatus 2 includes an image processing IC (integrated circuit) 3, an external interface 4, an external storage device 5, a memory 6, and a ROM (read only memory) 7. The external interface 4 is connected to the camera 1 and supplies the image data 21 received from the camera 1 to the image processing IC 3. The external storage device 5 stores data generated in the image processing in the image processing device 2. Data stored in the external storage device 5 includes vehicle specification data 22. The memory 6 is used as a working area for arithmetic processing by the image processing IC 3. The ROM 7 stores a program executed by the image processing IC 3. The program stored in the ROM 7 includes a vehicle specification measurement processing program 7a that is a program for executing image processing for measuring vehicle specifications.
なお、上記には、画像データ21から車両の諸元を算出するための画像処理装置2の構成が説明されているが、画像処理装置2において、車両諸元データ22を利用した車種判別も行われてもよい。この場合、車種判別に必要なプログラムは、ROM7にインストールされていてもよい。
In the above description, the configuration of the image processing apparatus 2 for calculating the vehicle specifications from the image data 21 is described. However, the image processing apparatus 2 also performs vehicle type determination using the vehicle specification data 22. It may be broken. In this case, a program necessary for vehicle type determination may be installed in the ROM 7.
このとき、ROM7として、(例えばフラッシュメモリのような)書き換え可能な不揮発性メモリが用いられても良い。この場合、車両諸元計測処理プログラム7a(及び必要であれば車種判別に用いられるプログラム)が、外部からROM7にインストールされても良い。車両諸元計測処理プログラム7aのROM7へのインストールには、車両諸元計測処理プログラム7aを記憶する記録媒体を用いても良い。この場合、当該記録媒体にアクセスするための装置が画像処理装置2に設けられる。また、ROM7の代わりに、適宜の記憶装置(例えば、ハードディスクドライブ(HDD)、ソリッドステートドライブ)を用いても良い。
At this time, a rewritable nonvolatile memory (such as a flash memory) may be used as the ROM 7. In this case, the vehicle specification measurement processing program 7a (and a program used for determining the vehicle type if necessary) may be installed in the ROM 7 from the outside. For installing the vehicle specification measurement processing program 7a in the ROM 7, a recording medium storing the vehicle specification measurement processing program 7a may be used. In this case, an apparatus for accessing the recording medium is provided in the image processing apparatus 2. Further, instead of the ROM 7, an appropriate storage device (for example, a hard disk drive (HDD) or a solid state drive) may be used.
画像処理IC3は、演算モジュール11と、画像入力インターフェース12と、データ入出力インターフェース13と、メモリコントローラ14と、ROMコントローラ15とを備えている。演算モジュール11と、画像入力インターフェース12と、データ入出力インターフェース13と、メモリコントローラ14と、ROMコントローラ15とは、内部バス16によって接続されている。演算モジュール11は、メモリ6をワーキングエリアとして使用しながら車両諸元計測処理プログラム7aを実行して、画像データ21から車両の諸元を算出するための画像処理を行う。画像入力インターフェース12は、カメラ1から画像データ21を受け取るインターフェースである。データ入出力インターフェース13は、外部記憶装置5へのアクセスを行うためのインターフェースである。メモリコントローラ14は、メモリ6へのアクセスを行うためのインターフェースである。また、ROMコントローラ15は、ROM7へのアクセスを行うためのインターフェースである。
The image processing IC 3 includes an arithmetic module 11, an image input interface 12, a data input / output interface 13, a memory controller 14, and a ROM controller 15. The arithmetic module 11, the image input interface 12, the data input / output interface 13, the memory controller 14, and the ROM controller 15 are connected by an internal bus 16. The calculation module 11 executes the vehicle specification measurement processing program 7 a while using the memory 6 as a working area, and performs image processing for calculating vehicle specifications from the image data 21. The image input interface 12 is an interface that receives image data 21 from the camera 1. The data input / output interface 13 is an interface for accessing the external storage device 5. The memory controller 14 is an interface for accessing the memory 6. The ROM controller 15 is an interface for accessing the ROM 7.
以下に述べられる車両の諸元を算出するための画像処理は、図2に示されているハードウェアを用いて実行される。以下では、車両の諸元を算出するための画像処理について、詳細に説明する。
The image processing for calculating the vehicle specifications described below is executed using the hardware shown in FIG. In the following, image processing for calculating vehicle specifications will be described in detail.
図3A、図3Bは、本発明の一実施形態における、車両の諸元を算出するための画像処理を示すフローチャートである。上述の車両諸元計測処理プログラム7aは、この画像処理を実行するためのプログラムコード群である。車両の諸元を算出するための画像処理は、大きく分けて、下記の3つのステージがある:
1.移動体検知用特徴点の検知及び追尾(図3AのステップS01~S04)
2.移動体の検知、分離、及び、諸元計測用特徴点の検知及び追尾(図3AのステップS05~S07)
3.諸元計測用特徴点に基づく車両の諸元の算出(図3BのステップS08~S12)
以下、それぞれのステージについて、詳細に説明する。 3A and 3B are flowcharts showing image processing for calculating vehicle specifications in one embodiment of the present invention. The above-mentioned vehicle specificationmeasurement processing program 7a is a program code group for executing this image processing. Image processing for calculating vehicle specifications is roughly divided into the following three stages:
1. Detection and tracking of feature points for moving object detection (steps S01 to S04 in FIG. 3A)
2. Detection and separation of moving objects, and detection and tracking of feature points for measurement (Steps S05 to S07 in FIG. 3A)
3. Calculation of vehicle specifications based on feature measurement feature points (steps S08 to S12 in FIG. 3B)
Hereinafter, each stage will be described in detail.
1.移動体検知用特徴点の検知及び追尾(図3AのステップS01~S04)
2.移動体の検知、分離、及び、諸元計測用特徴点の検知及び追尾(図3AのステップS05~S07)
3.諸元計測用特徴点に基づく車両の諸元の算出(図3BのステップS08~S12)
以下、それぞれのステージについて、詳細に説明する。 3A and 3B are flowcharts showing image processing for calculating vehicle specifications in one embodiment of the present invention. The above-mentioned vehicle specification
1. Detection and tracking of feature points for moving object detection (steps S01 to S04 in FIG. 3A)
2. Detection and separation of moving objects, and detection and tracking of feature points for measurement (Steps S05 to S07 in FIG. 3A)
3. Calculation of vehicle specifications based on feature measurement feature points (steps S08 to S12 in FIG. 3B)
Hereinafter, each stage will be described in detail.
1.移動体検知用特徴点の検知及び追尾
図3Aを参照して、まず、画像処理装置2の初期化が行われた後(ステップS01)、車両を撮影したフレーム画像の画像データ21が逐次に取り込まれる(ステップS02)。更に、画像データ21に示されているフレーム画像に含まれる特徴点が検知され、更に、各特徴点が追尾される(ステップS03)。ただし、ステップS03で検知され、追尾される特徴点は、上述の諸元計測用特徴点に一致するとは限らない。そこで、諸元計測用特徴点と区別するために、ステップS03で検知され、追尾される特徴点を、以下、移動体検知用特徴点と呼ぶ。ステップS03では、検知され、追尾される移動体検知用特徴点を列挙したリストである移動体検知用特徴点リスト23が生成される。移動体(多くの場合、車両)が進入してきた領域において新たに移動体検知用特徴点が検知されると、該移動体検知用特徴点が移動体検知用特徴点リスト23に追加される。また、画像の外に消えた移動体検知用特徴点又は追尾に失敗した移動体検知用特徴点は、移動体検知用特徴点リスト23から除去される。 1. Detecting and Tracking Feature Points for Moving Object Detection Referring to FIG. 3A, first, afterimage processing device 2 is initialized (step S01), image data 21 of a frame image obtained by photographing a vehicle is sequentially captured. (Step S02). Further, feature points included in the frame image shown in the image data 21 are detected, and each feature point is tracked (step S03). However, the feature points detected and tracked in step S03 do not necessarily match the above-described feature measurement feature points. Therefore, in order to distinguish from feature measurement feature points, the feature points detected and tracked in step S03 are hereinafter referred to as moving object detection feature points. In step S03, a moving object detection feature point list 23, which is a list in which the detected and tracked moving object detection feature points are listed, is generated. When a moving object detection feature point is newly detected in an area where a moving object (in many cases, a vehicle) has entered, the moving object detection feature point is added to the moving object detection feature point list 23. In addition, the moving object detection feature point that has disappeared outside the image or the moving object detection feature point that has failed to be tracked is removed from the moving object detection feature point list 23.
図3Aを参照して、まず、画像処理装置2の初期化が行われた後(ステップS01)、車両を撮影したフレーム画像の画像データ21が逐次に取り込まれる(ステップS02)。更に、画像データ21に示されているフレーム画像に含まれる特徴点が検知され、更に、各特徴点が追尾される(ステップS03)。ただし、ステップS03で検知され、追尾される特徴点は、上述の諸元計測用特徴点に一致するとは限らない。そこで、諸元計測用特徴点と区別するために、ステップS03で検知され、追尾される特徴点を、以下、移動体検知用特徴点と呼ぶ。ステップS03では、検知され、追尾される移動体検知用特徴点を列挙したリストである移動体検知用特徴点リスト23が生成される。移動体(多くの場合、車両)が進入してきた領域において新たに移動体検知用特徴点が検知されると、該移動体検知用特徴点が移動体検知用特徴点リスト23に追加される。また、画像の外に消えた移動体検知用特徴点又は追尾に失敗した移動体検知用特徴点は、移動体検知用特徴点リスト23から除去される。 1. Detecting and Tracking Feature Points for Moving Object Detection Referring to FIG. 3A, first, after
画像データ21の取り込み(ステップS02)、及び、移動体検知用特徴点の検知及び追尾(ステップS03)は、画像処理装置2に終了信号が与えられるまで逐次に行われる。画像処理装置2に終了信号が与えられると(ステップS04)、画像処理装置2における画像処理が終了する。
The capturing of the image data 21 (step S02) and the detection and tracking of the moving object detection feature point (step S03) are sequentially performed until an end signal is given to the image processing apparatus 2. When the end signal is given to the image processing apparatus 2 (step S04), the image processing in the image processing apparatus 2 is ended.
2.移動体の検知、分離、及び、諸元計測用特徴点の検知及び追尾
このステージでは、移動体検知用特徴点リスト23に列挙されている移動体検知用特徴点、即ち、現在、追尾されている移動体検知用特徴点の中から、各車両に対応する特徴点が検出される。詳細には、まず、移動体検知用特徴点リスト23に列挙されている移動体検知用特徴点のうち、車両に対応する特徴点(即ち、車両に対応しない特徴点を除く特徴点)が、移動特徴点として検出される(ステップS05)。より具体的には、移動体検知用特徴点リスト23に列挙されている移動体検知用特徴点のうち、静止している特徴点、及び、移動しているが車両の動きとは異なる動きをしている特徴点が除去される。道路を走行する車両は、概ね道路の向きに動くので、このような動きをしない特徴点は、車両に対応していない特徴点であると判別可能である。 2. Detection and separation of moving objects, detection and tracking of feature points for measurement of characteristics At this stage, moving object detection feature points listed in the moving object detectionfeature point list 23, that is, currently tracked The feature point corresponding to each vehicle is detected from the moving object detection feature points. Specifically, first, among the moving object detection feature points listed in the moving object detection feature point list 23, feature points corresponding to the vehicle (that is, feature points excluding feature points not corresponding to the vehicle) are: It is detected as a moving feature point (step S05). More specifically, among the moving object detection feature points listed in the moving object detection feature point list 23, the stationary feature points and the movements that are different from the movements of the vehicle are shown. The feature points are removed. Since the vehicle traveling on the road generally moves in the direction of the road, it is possible to determine that a feature point that does not move is a feature point that does not correspond to the vehicle.
このステージでは、移動体検知用特徴点リスト23に列挙されている移動体検知用特徴点、即ち、現在、追尾されている移動体検知用特徴点の中から、各車両に対応する特徴点が検出される。詳細には、まず、移動体検知用特徴点リスト23に列挙されている移動体検知用特徴点のうち、車両に対応する特徴点(即ち、車両に対応しない特徴点を除く特徴点)が、移動特徴点として検出される(ステップS05)。より具体的には、移動体検知用特徴点リスト23に列挙されている移動体検知用特徴点のうち、静止している特徴点、及び、移動しているが車両の動きとは異なる動きをしている特徴点が除去される。道路を走行する車両は、概ね道路の向きに動くので、このような動きをしない特徴点は、車両に対応していない特徴点であると判別可能である。 2. Detection and separation of moving objects, detection and tracking of feature points for measurement of characteristics At this stage, moving object detection feature points listed in the moving object detection
図4は、ステップS05における移動特徴点の検出の例を示す図である。図4の左図に示されているように、ステップS03において、一連の画像において特徴点41が検知され、更に、移動している特徴点41については追尾が行われる。図4の左図において、追尾が行われている特徴点41は、互いに線分で結ばれて図示されている。静止していると判断された特徴点は、移動体検知用特徴点リスト23から除去される。
FIG. 4 is a diagram showing an example of detection of moving feature points in step S05. As shown in the left diagram of FIG. 4, in step S03, the feature point 41 is detected in the series of images, and the tracking is performed for the moving feature point 41. In the left diagram of FIG. 4, the feature points 41 that are being tracked are connected to each other by line segments. The feature points determined to be stationary are removed from the moving object detection feature point list 23.
更に、追尾されている特徴点のうち、下記の条件(1)~(3)を満たす特徴点が、車両に対応する移動特徴点として検出される:
(1)所定数NSTD以上の連続したフレーム画像に渡って追尾ができていること(所定数NSTDは、パラメータとして与えられる)。
(2)開始点(当該特徴点について画像上で追尾が開始された位置)と、現在点(即ち、当該特徴点の画像上の最新の位置)とを結ぶベクトルの大きさが、μ×NTRC以上であること。ここで、μは、所定のパラメータ値(技術的には、単位時間当たりの移動量の閾値を意味している)であり、NTRCは、当該特徴点について追尾が行われているフレーム画像の数である。
(3)開始点から現在点に向かうベクトルと、開始点から画像の消失点に向かうベクトルとがなす角度が所定の閾値角度以下であること。ここでいう画像の消失点とは、車両の画像を透視図と近似した場合において、当該透視図に規定される消失点を意味している。図4の右図には、消失点43が図示されている。 Further, among the tracked feature points, feature points satisfying the following conditions (1) to (3) are detected as moving feature points corresponding to the vehicle:
(1) that it can track over a predetermined number N STD more consecutive frame images (the predetermined number N STD is given as a parameter).
(2) The size of a vector connecting the start point (the position where tracking of the feature point is started on the image) and the current point (that is, the latest position of the feature point on the image) is μ × N Be TRC or higher. Here, μ is a predetermined parameter value (technically means a threshold of movement amount per unit time), and NTRC is a frame image for which tracking is performed for the feature point. Is a number.
(3) The angle formed by the vector from the start point to the current point and the vector from the start point to the vanishing point of the image is equal to or less than a predetermined threshold angle. The vanishing point of the image here means a vanishing point defined in the perspective view when the image of the vehicle is approximated to the perspective view. The vanishing point 43 is illustrated on the right side of FIG.
(1)所定数NSTD以上の連続したフレーム画像に渡って追尾ができていること(所定数NSTDは、パラメータとして与えられる)。
(2)開始点(当該特徴点について画像上で追尾が開始された位置)と、現在点(即ち、当該特徴点の画像上の最新の位置)とを結ぶベクトルの大きさが、μ×NTRC以上であること。ここで、μは、所定のパラメータ値(技術的には、単位時間当たりの移動量の閾値を意味している)であり、NTRCは、当該特徴点について追尾が行われているフレーム画像の数である。
(3)開始点から現在点に向かうベクトルと、開始点から画像の消失点に向かうベクトルとがなす角度が所定の閾値角度以下であること。ここでいう画像の消失点とは、車両の画像を透視図と近似した場合において、当該透視図に規定される消失点を意味している。図4の右図には、消失点43が図示されている。 Further, among the tracked feature points, feature points satisfying the following conditions (1) to (3) are detected as moving feature points corresponding to the vehicle:
(1) that it can track over a predetermined number N STD more consecutive frame images (the predetermined number N STD is given as a parameter).
(2) The size of a vector connecting the start point (the position where tracking of the feature point is started on the image) and the current point (that is, the latest position of the feature point on the image) is μ × N Be TRC or higher. Here, μ is a predetermined parameter value (technically means a threshold of movement amount per unit time), and NTRC is a frame image for which tracking is performed for the feature point. Is a number.
(3) The angle formed by the vector from the start point to the current point and the vector from the start point to the vanishing point of the image is equal to or less than a predetermined threshold angle. The vanishing point of the image here means a vanishing point defined in the perspective view when the image of the vehicle is approximated to the perspective view. The vanishing point 43 is illustrated on the right side of FIG.
図4の右図は、ステップS05において検出される移動特徴点の例を示している。図4の右図には、所定数以上の連続したフレーム画像に渡って追尾されている特徴点42a、42b、42cが図示されている。ここで、符号42a-1は、特徴点42aの開始点を示しており、符号42a-3は、特徴点42aの現在点を示している。符号42a-2は、開始点に対応するフレーム画像と現在点に対応するフレーム画像の間のフレーム画像における特徴点42aの位置を示している。同様に、符号42b-1は、特徴点42bの開始点を示しており、符号42b-3は、特徴点42bの現在点を示している。符号42b-2は、開始点に対応するフレーム画像と現在点に対応するフレーム画像の間のフレーム画像における特徴点42bの位置を示している。更に、符号42c-1は、特徴点42cの開始点を示しており、符号42c-3は、特徴点42cの現在点を示している。符号42c-2は、開始点に対応するフレーム画像と現在点に対応するフレーム画像の間のフレーム画像における特徴点42cの位置を示している。
The right diagram of FIG. 4 shows an example of the moving feature points detected in step S05. The right diagram in FIG. 4 illustrates feature points 42a, 42b, and 42c that are tracked over a predetermined number of consecutive frame images. Here, reference numeral 42a-1 indicates the start point of the feature point 42a, and reference numeral 42a-3 indicates the current point of the feature point 42a. Reference numeral 42a-2 indicates the position of the feature point 42a in the frame image between the frame image corresponding to the start point and the frame image corresponding to the current point. Similarly, reference numeral 42b-1 indicates the start point of the feature point 42b, and reference numeral 42b-3 indicates the current point of the feature point 42b. Reference numeral 42b-2 indicates the position of the feature point 42b in the frame image between the frame image corresponding to the start point and the frame image corresponding to the current point. Further, reference numeral 42c-1 indicates the start point of the feature point 42c, and reference numeral 42c-3 indicates the current point of the feature point 42c. Reference numeral 42c-2 indicates the position of the feature point 42c in the frame image between the frame image corresponding to the start point and the frame image corresponding to the current point.
特徴点42aについては、開始点42a-1と現在点42a-3とを結ぶベクトルの大きさが、μ×NTR以上であるかの判断、及び、開始点42a-1から現在点42a-3に向かうベクトルと開始点42a-1から消失点43に向かうベクトルの間の角度が、所定の閾値θTH1以下であるかの判断が行われる。これらの判断に基づき、特徴点42aが移動特徴点として抽出されるか否かが判断される。
For the feature point 42a, a determination is made as to whether the magnitude of the vector connecting the start point 42a-1 and the current point 42a-3 is equal to or larger than μ × N TR , and the start point 42a-1 to the current point 42a-3. A determination is made as to whether the angle between the vector going to and the vector going from the start point 42a-1 to the vanishing point 43 is less than or equal to a predetermined threshold value θTH1 . Based on these determinations, it is determined whether or not the feature points 42a are extracted as moving feature points.
特徴点42b、42cについても、同様の判断が行われる。以下では、ステップS05において、特徴点42a、42b、42cが移動特徴点として検出されたとして説明を行う。
The same determination is made for the feature points 42b and 42c. In the following description, it is assumed that the feature points 42a, 42b, and 42c are detected as moving feature points in step S05.
図3Aに示されているように、移動特徴点の検出(ステップS05)の後、検出された移動特徴点のクラスタリングが行われる。(ステップS06)。図5を参照して、このクラスタリングは、各特徴点の消失点43までの距離と、開始点から現在点に向かうベクトルの向きとに基づいて行われる。なお、特徴点の消失点43までの距離としては、現在点から消失点43までの距離(図5では、距離DMとして図示されている)を用いても良いし、開始点から消失点43までの距離が用いられても良いし、また、特徴点の追尾の間の平均の距離が用いられても良い。このクラスタリングにより、1台の車両に対応する一群の特徴点が、同一のクラスタに分類される。
As shown in FIG. 3A, after detection of the moving feature points (step S05), clustering of the detected moving feature points is performed. (Step S06). Referring to FIG. 5, this clustering is performed based on the distance from each feature point to vanishing point 43 and the direction of the vector from the start point to the current point. As the distance to the vanishing point 43 of the feature points, (in FIG. 5, it is shown as the distance D M) distance from the current point to the vanishing point 43 may be used, vanishing point from the start point 43 May be used, or an average distance between tracking feature points may be used. By this clustering, a group of feature points corresponding to one vehicle is classified into the same cluster.
図5は、ステップS06におけるクラスタリングの例を示している。図5を参照して、ステップS05において、6つの特徴点:特徴点42a、42b、42c、42d、42e、42fが抽出されたとする。この場合、特徴点42a、42b、42c、42d、42e、42fのそれぞれについて、消失点43までの距離と、開始点から現在点に向かうベクトルの向きが算出される。図5では各特徴点の消失点43までの距離は、現在点から消失点43までの距離DMとして定義され、また、開始点から現在点に向かうベクトルの向きは、画像の水平方向からの角度として定義されている。
FIG. 5 shows an example of clustering in step S06. Referring to FIG. 5, it is assumed that six feature points: feature points 42a, 42b, 42c, 42d, 42e, and 42f are extracted in step S05. In this case, for each of the feature points 42a, 42b, 42c, 42d, 42e, and 42f, the distance to the vanishing point 43 and the direction of the vector from the start point to the current point are calculated. The distance to the vanishing point 43 in FIG. 5, each of the feature points is defined as the distance D M from the current point to the vanishing point 43, also the direction of the vector from the start point to the current point, the image from the horizontal direction It is defined as an angle.
例えば、特徴点42aについては、現在点42a-3から消失点43までの距離と、開始点42a-1から現在点42a-3に向かうベクトルと画面の水平方向との角度θが算出される。他の特徴点42b、42c、42d、42e、42fについても、同様に、現在点から消失点43までの距離と、開始点から現在点に向かうベクトルの向きが算出される。算出された現在点から消失点43までの距離と開始点から現在点に向かうベクトルの向きに基づいて、特徴点42a、42b、42c、42d、42e、42fのクラスタリングが行われる。図5の例では、クラスタリングの結果、特徴点42a、42b、42cが、第1の車両に対応するクラスタに分類され、特徴点42d、42e、42fが、第2の車両に対応するクラスタに分類されることになる。
For example, for the feature point 42a, the distance from the current point 42a-3 to the vanishing point 43 and the angle θ between the vector from the start point 42a-1 to the current point 42a-3 and the horizontal direction of the screen are calculated. Similarly for the other feature points 42b, 42c, 42d, 42e, 42f, the distance from the current point to the vanishing point 43 and the direction of the vector from the start point to the current point are calculated. Based on the calculated distance from the current point to the vanishing point 43 and the direction of the vector from the start point toward the current point, clustering of the feature points 42a, 42b, 42c, 42d, 42e, and 42f is performed. In the example of FIG. 5, as a result of clustering, the feature points 42a, 42b, and 42c are classified into clusters corresponding to the first vehicle, and the feature points 42d, 42e, and 42f are classified into clusters corresponding to the second vehicle. Will be.
図3Aに示されているように、移動特徴点のクラスタリングの後、各車両に対応する移動領域が画像から抽出され、更に、各移動領域について諸元計測用特徴点の検出と追尾が行われる(ステップS07)。
As shown in FIG. 3A, after clustering of moving feature points, moving regions corresponding to each vehicle are extracted from the image, and further, feature-measurement feature points are detected and tracked for each moving region. (Step S07).
まず、図6に示されているように、各クラスタの移動特徴点から、各画像において当該車両が撮影されている領域である移動領域が抽出される。移動領域は、各クラスタについて抽出される。移動領域は、画像における車両の輪郭に対応する多角形の形状の領域として抽出される。このとき、各クラスタの移動特徴点が、該多角形の頂点となるように移動領域が抽出される。
First, as shown in FIG. 6, a moving area that is an area where the vehicle is photographed in each image is extracted from the moving feature points of each cluster. A moving area is extracted for each cluster. The moving area is extracted as a polygonal area corresponding to the contour of the vehicle in the image. At this time, the moving region is extracted so that the moving feature point of each cluster becomes the vertex of the polygon.
更に、各車両に対応する移動領域について、上述の諸元計測用特徴点を検出する処理、及び、追尾する処理が行われる。ここで、図1Aを参照して説明したように、諸元計測用特徴点#1、#2は、それぞれ、車両の側面31、32にある特徴点であり、諸元計測用特徴点#3は、車両の下面33にある特徴点である。また、諸元計測用特徴点#4は、車両の前面34にある特徴点であり、諸元計測用特徴点#5は、車両の後面35にある特徴点である。更に、諸元計測用特徴点#6は、車両の上面36にある特徴点である。抽出される諸元計測用特徴点#1の数は、必ずしも一つには限定されず、複数の諸元計測用特徴点#1が抽出されても良いことに留意されたい。他の諸元計測用特徴点#2~#6についても同様である。
Furthermore, the above-described process for detecting feature points for measurement and the process of tracking are performed for the movement region corresponding to each vehicle. Here, as described with reference to FIG. 1A, the feature measurement feature points # 1 and # 2 are feature points on the side surfaces 31 and 32 of the vehicle, respectively, and the feature measurement feature point # 3. Is a feature point on the lower surface 33 of the vehicle. The feature measurement feature point # 4 is a feature point on the front surface 34 of the vehicle, and the feature measurement feature point # 5 is a feature point on the rear surface 35 of the vehicle. Furthermore, feature measurement feature point # 6 is a feature point on the upper surface 36 of the vehicle. It should be noted that the number of feature measurement feature points # 1 to be extracted is not necessarily limited to one, and a plurality of feature measurement feature points # 1 may be extracted. The same applies to the other feature measurement feature points # 2 to # 6.
ここで、諸元計測用特徴点の追尾は、各フレーム画像について諸元計測用特徴点の検出し、フレーム画像の間で諸元計測用特徴点を対応づける手法によっても行われても良い。また、諸元計測用特徴点の追尾は、移動領域が最初に出現したフレーム画像(初期フレーム画像)について諸元計測用特徴点を検出し、後続のフレーム画像において該諸元計測用特徴点について動体追尾を行う手法によって行われても良い。
Here, the tracking of the feature point for specification measurement may be performed by a method of detecting the feature point for specification measurement of each frame image and associating the feature point for specification measurement between the frame images. In addition, tracking of feature measurement feature points is performed by detecting feature measurement feature points for a frame image (initial frame image) in which a moving region first appears, and for the feature measurement feature points in subsequent frame images. It may be performed by a technique for tracking a moving object.
いずれの場合についても、少なくとも初期フレームについて諸元計測用特徴点を検出する処理が行われるので、以下では、まず、諸元計測用特徴点を検出する処理について説明する。諸元計測用特徴点を検出する処理は、下記の手法(1)~(3)の少なくとも一つを利用して行われる。ここで、抽出される諸元計測用特徴点#1の数は、必ずしも一つには限定されず、複数の諸元計測用特徴点#1が抽出されても良いことに留意されたい。したがって、下記の手法(1)~(3)の複数が用いられて複数の諸元計測用特徴点#1が抽出されても良い。他の諸元計測用特徴点#2~#6についても同様である。
In any case, since the process for detecting the feature points for specification measurement is performed at least for the initial frame, first, the process for detecting the feature points for specification measurement will be described first. The process of detecting feature measurement feature points is performed using at least one of the following methods (1) to (3). Here, it should be noted that the number of feature measurement feature points # 1 to be extracted is not necessarily limited to one, and a plurality of feature measurement feature points # 1 may be extracted. Therefore, a plurality of feature measurement feature points # 1 may be extracted by using a plurality of the following methods (1) to (3). The same applies to the other feature measurement feature points # 2 to # 6.
手法(1):
諸元計測用特徴点を検出する手法(1)では、各車両に接する接線を抽出すると共に該接線が交わる交点が求められる。諸元計測用特徴点は、求められた交点のうちから選択されて決定される。ここでいう「接線」とは、実空間において車両に接する接線に対応している画像内の線を意味している。図7A、図7Bは、車両に接する接線及びそれらの交点を求める処理の例を示している。該接線は、画像内においても移動領域に接する接線である場合もあるが(符号61~66で示された接線)、必ずしも、それに限定されない(例えば、符号67~69で示された接線)。 Method (1):
In the method (1) of detecting feature measurement feature points, a tangent line that contacts each vehicle is extracted and an intersection point at which the tangent line intersects is obtained. The feature measurement feature points are selected and determined from the obtained intersections. Here, “tangent” means a line in the image corresponding to a tangent that contacts the vehicle in real space. FIG. 7A and FIG. 7B show an example of processing for obtaining tangent lines that contact the vehicle and their intersections. The tangent may be a tangent tangent to the moving region in the image (tangent indicated byreference numerals 61 to 66), but is not necessarily limited thereto (for example, tangent indicated by reference numerals 67 to 69).
諸元計測用特徴点を検出する手法(1)では、各車両に接する接線を抽出すると共に該接線が交わる交点が求められる。諸元計測用特徴点は、求められた交点のうちから選択されて決定される。ここでいう「接線」とは、実空間において車両に接する接線に対応している画像内の線を意味している。図7A、図7Bは、車両に接する接線及びそれらの交点を求める処理の例を示している。該接線は、画像内においても移動領域に接する接線である場合もあるが(符号61~66で示された接線)、必ずしも、それに限定されない(例えば、符号67~69で示された接線)。 Method (1):
In the method (1) of detecting feature measurement feature points, a tangent line that contacts each vehicle is extracted and an intersection point at which the tangent line intersects is obtained. The feature measurement feature points are selected and determined from the obtained intersections. Here, “tangent” means a line in the image corresponding to a tangent that contacts the vehicle in real space. FIG. 7A and FIG. 7B show an example of processing for obtaining tangent lines that contact the vehicle and their intersections. The tangent may be a tangent tangent to the moving region in the image (tangent indicated by
図7A、図7Bの(1)欄に図示されているように、手法(1)では、まず、実空間において、路面上にあり、且つ、車線に平行であるような線に対応する接線61、62が抽出される。実空間において、路面上にあり且つ車線に平行な線が画像においてどのような角度で撮像されるかは、カメラ1の空間的配置により決定されるから、予め分かっている情報である。この事実を利用して、路面上にあり且つ車線に平行な線に対応する接線が抽出される。ここで、接線61は、抽出された車線に平行な線に対応する接線のうち、(カメラ1から見たときに)車両の手前側にある接線であり、接線62は、車両の向こう側にある接線である。
As shown in the column (1) of FIGS. 7A and 7B, in the method (1), first, in a real space, a tangent 61 corresponding to a line that is on the road surface and parallel to the lane. , 62 are extracted. In real space, the angle at which a line on the road surface and parallel to the lane is captured in the image is determined by the spatial arrangement of the camera 1, and is information that is known in advance. Using this fact, a tangent corresponding to a line on the road surface and parallel to the lane is extracted. Here, the tangent 61 is a tangent on the near side of the vehicle (when viewed from the camera 1) among the tangents corresponding to the line parallel to the extracted lane, and the tangent 62 is on the far side of the vehicle. A tangent.
更に、図7A、図7Bの(2)欄に図示されているように、実空間において、路面上にあり、且つ、車線に垂直であるような線に対応する接線が抽出される。実空間において車線に平行な線と同様に、実空間において車線に垂直な線が画像においてどのような角度で撮像されるかは、カメラ1の空間的配置により決定され、予め分かっている情報である。この事実を利用して、実空間において車線に垂直な線に対応する接線が抽出される。図7A、図7Bの(2)欄では、接線63は、抽出された車線に垂直な線に対応する接線のうち、(カメラ1から見たときに)車両の手前側にある接線であり、接線64は、車両の向こう側にある接線である。
Furthermore, as shown in the column (2) of FIGS. 7A and 7B, a tangent corresponding to a line that is on the road surface and is perpendicular to the lane is extracted in the real space. As with lines parallel to the lane in the real space, the angle at which the line perpendicular to the lane is captured in the real space is determined by the spatial arrangement of the camera 1 and is known in advance. is there. Using this fact, a tangent corresponding to a line perpendicular to the lane in the real space is extracted. In the column (2) of FIGS. 7A and 7B, the tangent 63 is a tangent on the near side of the vehicle (when viewed from the camera 1) among the tangents corresponding to the line perpendicular to the extracted lane, Tangent line 64 is a tangent line on the other side of the vehicle.
加えて、接線61と接線63の交点51が求められ、接線62、64の交点52が求められる。
In addition, the intersection 51 of the tangent 61 and the tangent 63 is obtained, and the intersection 52 of the tangents 62 and 64 is obtained.
更に、図7A、図7Bの(3)欄に図示されているように、実空間において路面に垂直であるような線に対応する接線が抽出される。実空間において路面に垂直な線が画像においてどのような角度で撮像されるかは、予め分かっている情報であるから、この事実を利用して、実空間において、車線に垂直な線に対応する移動領域の接線を抽出することができる。図7A、図7Bの(3)欄では、抽出された路面に垂直であるような線に対応する接線のうち、車両の向こう側にある接線が符号65で示されており、車両の手前側にある接線が符号66、67で示されている。ここで、接線67は、車両の手前側にある接線61、63の交点51を通過するような線として抽出される。
Furthermore, as illustrated in the column (3) of FIGS. 7A and 7B, a tangent corresponding to a line that is perpendicular to the road surface in the real space is extracted. Since the angle perpendicular to the road surface in the real space is captured in the image is information that is known in advance, this fact is used to correspond to the line perpendicular to the lane in the real space. The tangent line of the moving area can be extracted. In the (3) column of FIGS. 7A and 7B, among the tangents corresponding to the lines that are perpendicular to the extracted road surface, the tangents on the far side of the vehicle are indicated by reference numeral 65, and the front side of the vehicle The tangent lines at 66 are indicated by reference numerals 66 and 67. Here, the tangent 67 is extracted as a line passing through the intersection 51 of the tangents 61 and 63 on the front side of the vehicle.
加えて、(3)欄に図示されているように、接線61と接線65の交点53、接線64と接線65の交点54、接線63と接線66の交点55、及び、接線62と接線66の交点56が求められる。
In addition, as shown in the column (3), the intersection 53 of the tangent 61 and the tangent 65, the intersection 54 of the tangent 64 and the tangent 65, the intersection 55 of the tangent 63 and the tangent 66, and the intersection 55 of the tangent 62 and the tangent 66 An intersection point 56 is determined.
更に、図7A、図7Bの(3)欄に図示されているように、実空間において路面の上方に離れて位置し、路面に平行な平面内にあり、且つ、車線に垂直又は平行な線に対応する接線68、69が抽出される。ここで、接線68は、車線に垂直な線に対応する接線であり、接線69は、車線に平行な線に対応する接線である。接線68は、交点56を通過するような線として抽出される。加えて、接線67、68の交点57が求められ、接線69は、交点57を通過するような線として抽出される。
Further, as shown in the column (3) of FIGS. 7A and 7B, a line that is located above the road surface in real space, is in a plane parallel to the road surface, and is perpendicular or parallel to the lane. Tangent lines 68 and 69 corresponding to are extracted. Here, the tangent 68 is a tangent corresponding to a line perpendicular to the lane, and the tangent 69 is a tangent corresponding to a line parallel to the lane. The tangent line 68 is extracted as a line passing through the intersection point 56. In addition, an intersection point 57 of the tangent lines 67 and 68 is obtained, and the tangent line 69 is extracted as a line passing through the intersection point 57.
図8A~図8Cは、求められた交点のうちから各諸元計測用特徴点を決定する手法を示す図である。詳細には、図8Aは、車両の側面31、32にある諸元計測用特徴点#1、#2、及び、車両の下面33にある諸元計測用特徴点#3の決定方法を示す図である。また、図8Bは、車両の前面34にある諸元計測用特徴点#4、車両の後面35にある諸元計測用特徴点#5の決定方法を示す図である。図8Cは、車両の上面36にある諸元計測用特徴点#6の決定方法を示す図である。なお、車両の下面33にある諸元計測用特徴点#3の決定方法は、図8Aのみならず、図8B、図8Cにも図示されている。
8A to 8C are diagrams showing a method for determining each feature measurement feature point from the obtained intersections. Specifically, FIG. 8A is a diagram showing a method for determining feature measurement feature points # 1 and # 2 on the side surfaces 31 and 32 of the vehicle and feature measurement feature point # 3 on the lower surface 33 of the vehicle. It is. FIG. 8B is a diagram showing a method for determining the feature measurement feature point # 4 on the front surface 34 of the vehicle and the feature measurement feature point # 5 on the rear surface 35 of the vehicle. FIG. 8C is a diagram illustrating a method of determining the feature measurement feature point # 6 on the upper surface 36 of the vehicle. The method for determining the feature measurement feature point # 3 on the lower surface 33 of the vehicle is illustrated not only in FIG. 8A but also in FIGS. 8B and 8C.
図8Aを参照して、上述のようにして求められた交点のうち車両の側面31にある交点(即ち、交点51、53、54、57)から諸元計測用特徴点#1が選択される。ここで、交点51、53、54、57の全てが諸元計測用特徴点#1として決定されてもよく、また、交点51、53、54、57のうちから適宜に選択された一又は複数の交点が諸元計測用特徴点#1として決定されてもよい。
Referring to FIG. 8A, feature measurement feature # 1 is selected from the intersections on the side surface 31 of the vehicle (that is, intersections 51, 53, 54, and 57) among the intersections obtained as described above. . Here, all of the intersection points 51, 53, 54, 57 may be determined as the feature measurement feature point # 1, or one or more appropriately selected from the intersection points 51, 53, 54, 57. May be determined as feature measurement feature point # 1.
更に、車両の側面32にある交点(即ち、交点52、55、56)のうちから諸元計測用特徴点#2が選択される。ここで、交点52、55、56の全てが諸元計測用特徴点#2として決定されてもよく、また、交点52、55、56のうちから適宜に選択された一又は複数の交点が諸元計測用特徴点#2として決定されてもよい。
Further, the feature measurement feature point # 2 is selected from the intersection points (that is, the intersection points 52, 55, and 56) on the side surface 32 of the vehicle. Here, all of the intersection points 52, 55, and 56 may be determined as the feature measurement feature point # 2, and one or a plurality of intersection points appropriately selected from the intersection points 52, 55, and 56 may be determined. The original measurement feature point # 2 may be determined.
また、車両の下面33にある交点(即ち、交点51、53、55)のうちから諸元計測用特徴点#3が選択される。ここで、交点51、53、55の全てが諸元計測用特徴点#3として決定されてもよく、また、交点51、53、55のうちから適宜に選択された一又は複数の交点が諸元計測用特徴点#3として決定されてもよい。
Also, the feature measurement feature point # 3 is selected from the intersection points (that is, the intersection points 51, 53, 55) on the lower surface 33 of the vehicle. Here, all of the intersection points 51, 53, and 55 may be determined as the feature measurement feature point # 3, and one or more intersection points appropriately selected from the intersection points 51, 53, and 55 may be determined. The original measurement feature point # 3 may be determined.
更に、図8Bに図示されているように、車両の前面34にある交点(即ち、交点52、53、54)のうちから諸元計測用特徴点#4が選択される。ここで、交点52、53、54の全てが諸元計測用特徴点#4として決定されてもよく、また、交点52、53、54のうちから適宜に選択された一又は複数の交点が諸元計測用特徴点#4として決定されてもよい。
Further, as shown in FIG. 8B, the feature measurement feature point # 4 is selected from the intersection points (that is, the intersection points 52, 53, 54) on the front surface 34 of the vehicle. Here, all of the intersection points 52, 53, and 54 may be determined as the feature measurement feature point # 4, and one or more intersection points appropriately selected from the intersection points 52, 53, and 54 may be determined. The original measurement feature point # 4 may be determined.
また、車両の後面35にある交点(即ち、交点51、55、56、57)のうちから諸元計測用特徴点#5が選択される。ここで、交点51、55、56、57の全てが諸元計測用特徴点#5として決定されてもよく、また、交点51、55、56、57のうちから適宜に選択された一又は複数の交点が諸元計測用特徴点#5として決定されてもよい。
Also, the feature measurement feature point # 5 is selected from the intersection points (that is, the intersection points 51, 55, 56, 57) on the rear surface 35 of the vehicle. Here, all of the intersection points 51, 55, 56, 57 may be determined as the feature measurement feature point # 5, and one or more appropriately selected from the intersection points 51, 55, 56, 57. May be determined as feature measurement feature point # 5.
更に、図8Cに図示されているように、車両の上面36にある交点(即ち、交点52、56、57)のうちから諸元計測用特徴点#6が選択される。ここで、交点52、56、57の全てが諸元計測用特徴点#6として決定されてもよく、また、交点52、56、57のうちから適宜に選択された一又は複数の交点が諸元計測用特徴点#6として決定されてもよい。
Further, as shown in FIG. 8C, the feature measurement feature point # 6 is selected from the intersection points (that is, the intersection points 52, 56, 57) on the upper surface 36 of the vehicle. Here, all of the intersection points 52, 56, and 57 may be determined as the feature measurement feature point # 6, and one or a plurality of intersection points appropriately selected from the intersection points 52, 56, and 57 may be determined. The original measurement feature point # 6 may be determined.
手法(2):
諸元計測用特徴点を検出する手法(2)では、手法(1)と同様にして接線、交点を求めた後、求められた接線及び交点で決まる探索路に沿って特徴点を探索することにより、より追尾しやすい特徴点が各面について探索される。この探索によって求められた特徴点が諸元計測用特徴点として決定される。図9A~図9Cは、手法(2)において各諸元計測用特徴点を決定する手法を示す図である。 Method (2):
In the method (2) for detecting feature measurement feature points, the tangent and intersection are obtained in the same manner as in the method (1), and then the feature points are searched along the search path determined by the obtained tangent and intersection. Thus, feature points that are easier to track are searched for for each surface. The feature points obtained by this search are determined as feature measurement feature points. 9A to 9C are diagrams showing a method for determining each feature measurement feature point in the method (2).
諸元計測用特徴点を検出する手法(2)では、手法(1)と同様にして接線、交点を求めた後、求められた接線及び交点で決まる探索路に沿って特徴点を探索することにより、より追尾しやすい特徴点が各面について探索される。この探索によって求められた特徴点が諸元計測用特徴点として決定される。図9A~図9Cは、手法(2)において各諸元計測用特徴点を決定する手法を示す図である。 Method (2):
In the method (2) for detecting feature measurement feature points, the tangent and intersection are obtained in the same manner as in the method (1), and then the feature points are searched along the search path determined by the obtained tangent and intersection. Thus, feature points that are easier to track are searched for for each surface. The feature points obtained by this search are determined as feature measurement feature points. 9A to 9C are diagrams showing a method for determining each feature measurement feature point in the method (2).
図9Aを参照して、側面31にある諸元計測用特徴点#1の決定においては、上記のようにして求められた接線のうち側面31にある部分で構成される経路が探索路として定められ、この探索路の周辺について特徴点の探索が行われる。このとき、交点は、この探索路の決定の際に、接線のうち側面31にある部分を得るために用いられる。より具体的には、接線65のうち交点54と交点53とを結ぶ部分、接線62のうち交点53と交点51とを結ぶ部分、及び、及び、接線67のうち、交点51と交点57とを結ぶ部分で構成される探索路の周辺について特徴点の探索が行われる。この探索によって得られた特徴点が、諸元計測用特徴点#1として決定される。決定される諸元計測用特徴点#1の数は1つでもよいし、複数であっても良い。
With reference to FIG. 9A, in the determination of the feature measurement feature point # 1 on the side surface 31, the route constituted by the portion on the side surface 31 of the tangent lines obtained as described above is determined as the search path. The feature points are searched for around the search path. At this time, the intersection is used to obtain a portion of the tangent line on the side surface 31 when determining the search path. More specifically, a portion connecting the intersection 54 and the intersection 53 in the tangent 65, a portion connecting the intersection 53 and the intersection 51 in the tangent 62, and the intersection 51 and the intersection 57 in the tangent 67. A search for feature points is performed around the search path formed by the connecting portions. The feature point obtained by this search is determined as feature measurement feature point # 1. The number of feature measurement feature points # 1 to be determined may be one or plural.
側面32にある諸元計測用特徴点#2の決定においては、求められた接線のうち側面32にある部分で構成される経路が探索路として定められ、この探索路の周辺について特徴点の探索が行われる。より具体的には、接線66のうち交点55と交点56とを結ぶ部分、及び、接線62のうち交点56と交点52とを結ぶ部分で構成される探索路の周辺について特徴点の探索が行われる。この探索によって得られた特徴点が、諸元計測用特徴点#2として決定される。決定される諸元計測用特徴点#2の数は1つでもよいし、複数であっても良い。
In determining the feature measurement feature point # 2 on the side surface 32, a route constituted by a portion on the side surface 32 of the obtained tangent lines is determined as a search route, and a feature point search is performed around the search route. Is done. More specifically, feature points are searched for in the vicinity of a search path constituted by a portion connecting the intersection point 55 and the intersection point 56 in the tangent line 66 and a portion connecting the intersection point 56 and the intersection point 52 in the tangent line 62. Is called. The feature point obtained by this search is determined as feature measurement feature point # 2. The number of feature measurement feature points # 2 to be determined may be one or plural.
更に、下面33にある諸元計測用特徴点#3の決定においては、求められた接線のうちの下面33にある部分で構成される経路が探索路として定められ、この探索路の周辺について特徴点の探索が行われる。より具体的には、接線61のうち交点53と交点51とを結ぶ部分、及び、接線63のうち交点51と交点55とを結ぶ部分で構成される探索路の周辺について特徴点の探索が行われる。この探索によって得られた特徴点が、諸元計測用特徴点#2として決定される。決定される諸元計測用特徴点#2の数は1つでもよいし、複数であっても良い。
Further, in the determination of the feature measurement feature point # 3 on the lower surface 33, a route constituted by a portion on the lower surface 33 of the obtained tangent lines is determined as a search route, and features around the search route are characterized. A point search is performed. More specifically, feature points are searched for in the vicinity of a search path constituted by a portion connecting the intersection 53 and the intersection 51 in the tangent 61 and a portion connecting the intersection 51 and the intersection 55 in the tangent 63. Is called. The feature point obtained by this search is determined as feature measurement feature point # 2. The number of feature measurement feature points # 2 to be determined may be one or plural.
更に、図9Bを参照して、前面34にある諸元計測用特徴点#4の決定においては、上記のようにして求められた接線のうち前面34にある部分で構成される経路が探索路として定められ、この探索路の周辺について特徴点の探索が行われる。より具体的には、接線65のうち交点53と交点54とを結ぶ部分、及び、接線64のうち交点54と交点52とを結ぶ部分で構成される探索路の周辺について特徴点の探索が行われる。この探索によって得られた特徴点が、諸元計測用特徴点#4として決定される。決定される諸元計測用特徴点#4の数は1つでもよいし、複数であっても良い。
Further, referring to FIG. 9B, in the determination of the feature measurement feature point # 4 on the front surface 34, the route constituted by the portion on the front surface 34 among the tangent lines obtained as described above is the search path. A search for feature points is performed around the search path. More specifically, feature points are searched for in the vicinity of a search path constituted by a portion connecting the intersection 53 and the intersection 54 in the tangent 65 and a portion connecting the intersection 54 and the intersection 52 in the tangent 64. Is called. The feature point obtained by this search is determined as feature measurement feature point # 4. The number of feature measurement feature points # 4 to be determined may be one or plural.
また、後面35にある諸元計測用特徴点#5の決定においては、求められた接線のうち後面35にある部分で構成される経路が探索路として定められ、この探索路の周辺について特徴点の探索が行われる。より具体的には、接線66のうち交点55と交点56とを結ぶ部分、接線68のうち交点56と交点57とを結ぶ部分、接線67のうち交点57と交点51とを結ぶ部分、及び、接線63のうち交点51と交点55とを結ぶ部分で構成される探索路の周辺について特徴点の探索が行われる。この探索によって得られた特徴点が、諸元計測用特徴点#5として決定される。決定される諸元計測用特徴点#5の数は1つでもよいし、複数であっても良い。
Further, in determining the feature measurement feature point # 5 on the rear surface 35, a route constituted by a portion on the rear surface 35 among the obtained tangent lines is determined as a search route, and feature points around the search route are feature points. Search is performed. More specifically, a portion connecting the intersection point 55 and the intersection point 56 in the tangent line 66, a portion connecting the intersection point 56 and the intersection point 57 in the tangent line 68, a portion connecting the intersection point 57 and the intersection point 51 in the tangent line 67, and A search for feature points is performed around the search path formed by the portion connecting the intersection 51 and the intersection 55 in the tangent line 63. A feature point obtained by this search is determined as feature measurement feature point # 5. The number of feature measurement feature points # 5 to be determined may be one or plural.
更に、図9Cを参照して、上面36にある諸元計測用特徴点#6の決定においては、求められた接線のうち上面36にある部分で構成される経路が探索路として定められ、この探索路の周辺について特徴点の探索が行われる。より具体的には、接線68のうち交点57と交点56とを結ぶ部分、及び、接線62のうち交点56と交点52とを結ぶ部分で構成される探索路の周辺について特徴点の探索が行われる。この探索によって得られた特徴点が、諸元計測用特徴点#6として決定される。決定される諸元計測用特徴点#6の数は1つでもよいし、複数であっても良い。
Furthermore, referring to FIG. 9C, in the determination of the feature measurement feature point # 6 on the upper surface 36, a route constituted by a portion on the upper surface 36 of the obtained tangent lines is determined as a search path. A feature point search is performed around the search path. More specifically, feature points are searched for in the vicinity of the search path composed of a portion connecting the intersection 57 and the intersection 56 in the tangent line 68 and a portion connecting the intersection 56 and the intersection 52 in the tangent line 62. Is called. The feature point obtained by this search is determined as feature measurement feature point # 6. The number of feature measurement feature points # 6 to be determined may be one or plural.
手法(3):
諸元計測用特徴点を検出する手法(3)では、車両の各面について、直接に(即ち、上述の手法(1)で求められるような接線、交点を参照せずに)特徴点の探索が行われる。この探索によって求められた特徴点が諸元計測用特徴点として決定される。図10~図11は、手法(3)において諸元計測用特徴点を決定する手法を示す図である。 Method (3):
In the method (3) for detecting feature measurement feature points, search for feature points is performed directly on each surface of the vehicle (that is, without referring to tangents and intersections as obtained in the above method (1)). Is done. The feature points obtained by this search are determined as feature measurement feature points. 10 to 11 are diagrams showing a method for determining feature measurement feature points in the method (3).
諸元計測用特徴点を検出する手法(3)では、車両の各面について、直接に(即ち、上述の手法(1)で求められるような接線、交点を参照せずに)特徴点の探索が行われる。この探索によって求められた特徴点が諸元計測用特徴点として決定される。図10~図11は、手法(3)において諸元計測用特徴点を決定する手法を示す図である。 Method (3):
In the method (3) for detecting feature measurement feature points, search for feature points is performed directly on each surface of the vehicle (that is, without referring to tangents and intersections as obtained in the above method (1)). Is done. The feature points obtained by this search are determined as feature measurement feature points. 10 to 11 are diagrams showing a method for determining feature measurement feature points in the method (3).
諸元計測用特徴点を検出する手法(3)が採用される場合、車両の各面に存在することが想定される部品のテンプレートのデータベースが用意され、該テンプレートを用いたテンプレートマッチングが行われる。図10は、用意されるテンプレートのデータベースの内容の例を概念的に示す図である。用意されるテンプレートのデータベースは、下記の6つのデータベースを含んでいる:
・カメラ側の側面31にある部品のテンプレートを含むテンプレートデータベース71
・カメラと反対側の側面32にある部品のテンプレートを含むテンプレートデータベース72
・下面33にある部品のテンプレートを含むテンプレートデータベース73
・前面34にある部品のテンプレートを含むテンプレートデータベース74
・後面35にある部品のテンプレートを含むテンプレートデータベース75
・上面36にある部品のテンプレートを含むテンプレートデータベース76
テンプレートデータベース71~76のそれぞれにおいて、各部品のテンプレートには、該テンプレートにおける特徴点の位置を示す特徴点位置データが添付される。 When the method (3) for detecting feature measurement feature points is employed, a template database of parts assumed to exist on each surface of the vehicle is prepared, and template matching is performed using the template. . FIG. 10 is a diagram conceptually illustrating an example of the contents of a prepared template database. The prepared database of templates includes the following six databases:
Atemplate database 71 including a template of parts on the side surface 31 on the camera side
Atemplate database 72 containing the template of the part on the side 32 opposite the camera
Atemplate database 73 containing the template of the part on the lower surface 33
Atemplate database 74 containing the template for the part on the front 34
Atemplate database 75 containing the template of the part on the rear surface 35
Atemplate database 76 containing the template of the part on the upper surface 36
In each of thetemplate databases 71 to 76, feature point position data indicating the position of the feature point in the template is attached to the template of each part.
・カメラ側の側面31にある部品のテンプレートを含むテンプレートデータベース71
・カメラと反対側の側面32にある部品のテンプレートを含むテンプレートデータベース72
・下面33にある部品のテンプレートを含むテンプレートデータベース73
・前面34にある部品のテンプレートを含むテンプレートデータベース74
・後面35にある部品のテンプレートを含むテンプレートデータベース75
・上面36にある部品のテンプレートを含むテンプレートデータベース76
テンプレートデータベース71~76のそれぞれにおいて、各部品のテンプレートには、該テンプレートにおける特徴点の位置を示す特徴点位置データが添付される。 When the method (3) for detecting feature measurement feature points is employed, a template database of parts assumed to exist on each surface of the vehicle is prepared, and template matching is performed using the template. . FIG. 10 is a diagram conceptually illustrating an example of the contents of a prepared template database. The prepared database of templates includes the following six databases:
A
A
A
A
A
A
In each of the
例えば、テンプレートデータベース71については、側面31にあると想定される部品(例えば、タイヤ、窓、ミラー、ライト)の画像から作成されたテンプレートが登録され、更に、各テンプレートに特徴点の位置が指定される。図10の黒点は、各テンプレートに定められた特徴点を示している。複数の車種に対応するために、テンプレートデータベース71においては、各部品について複数のテンプレートが用意される。他のテンプレートデータベース72~76についても同様に、各面にあると想定される部品の画像から作成されたテンプレートが登録され、各テンプレートに特徴点が指定される。テンプレートデータベース71~76は、適宜の記憶手段、例えば、図2に図示されている外部記憶装置5に記憶される。
For example, for the template database 71, templates created from images of parts (eg, tires, windows, mirrors, lights) that are assumed to be on the side surface 31 are registered, and the positions of feature points are specified for each template. Is done. Black points in FIG. 10 indicate feature points defined in each template. In order to correspond to a plurality of vehicle types, a plurality of templates are prepared for each part in the template database 71. Similarly, in the other template databases 72 to 76, templates created from images of parts assumed to be on each surface are registered, and feature points are designated for each template. The template databases 71 to 76 are stored in appropriate storage means, for example, the external storage device 5 shown in FIG.
図11は、テンプレートマッチングによる諸元計測用特徴点の検出を概念的に説明する図である。なお、図11は、テンプレートデータベース75に登録されたテンプレートを用いた、後面35にある諸元計測用特徴点#5の検出を図示している。後面35にある諸元計測用特徴点#5では、処理対象のフレーム画像の全体に対して、テンプレートデータベース75に含まれるテンプレート(即ち、後面35にある部品のテンプレート)とのマッチング処理が行われる。各フレーム画像の各位置について各テンプレートについて類似度が求められ、各部品について、最もマッチするテンプレートと、該テンプレートの位置(マッチング位置)が算出される。更に、最もマッチするテンプレートの位置と、該テンプレートについて特徴点位置データによって指定された特徴点の位置から、諸元計測用特徴点の位置が決定される。このような手順により、諸元計測用特徴点が検出される。
FIG. 11 is a diagram conceptually illustrating detection of feature points for specification measurement by template matching. FIG. 11 illustrates detection of feature measurement feature point # 5 on the rear surface 35 using a template registered in the template database 75. At the feature measurement feature point # 5 on the rear surface 35, the entire processing target frame image is subjected to matching processing with a template included in the template database 75 (that is, a component template on the rear surface 35). . Similarity is obtained for each template for each position of each frame image, and for each part, the most matching template and the position (matching position) of the template are calculated. Further, the position of the feature measuring feature point is determined from the position of the template that best matches and the position of the feature point designated by the feature point position data for the template. According to such a procedure, feature measurement feature points are detected.
以上には、後面35にある諸元計測用特徴点#5の検出について説明しているが、他の面(側面31、32、下面33、前面34、上面36)についても同様にしてテンプレートマッチングによる諸元計測用特徴点の検出が行われる。
In the above, the detection of the feature measurement feature point # 5 on the rear surface 35 has been described, but the template matching is similarly performed for the other surfaces (side surfaces 31, 32, lower surface 33, front surface 34, upper surface 36). Detection of feature points for specification measurement is performed.
上記の手法(1)~(3)による諸元計測用特徴点の検出は、各フレーム画像について行われても良い。この場合、諸元計測用特徴点の追尾は、フレーム画像の間で諸元計測用特徴点を対応づける手法によっても行われる。
Detecting feature measurement feature points by the above methods (1) to (3) may be performed for each frame image. In this case, tracking of feature measurement feature points is also performed by a method of associating feature measurement feature points between frame images.
上記の手法(1)~(3)による諸元計測用特徴点の検出は、移動領域が最初に出現したフレーム画像(初期フレーム画像)について行われても良い。この場合、後続のフレーム画像については、検出された諸元計測用特徴点について適宜のアルゴリズムを用いた動体追尾が行われる。ステップS07における諸元計測用特徴点の検出及び追尾は、以上のようにして行われる。
Detecting feature measurement feature points by the above methods (1) to (3) may be performed on a frame image (initial frame image) in which a moving region first appears. In this case, with respect to the subsequent frame image, moving object tracking is performed on the detected feature measurement feature points using an appropriate algorithm. The detection and tracking of the characteristic measurement feature points in step S07 are performed as described above.
図3Aを再度に参照して、ステップS07における諸元計測用特徴点の検出と追尾が行われると、諸元計測用特徴点の検出と追尾の履歴データ、即ち、各時刻におけるフレーム画像における諸元計測用特徴点の位置を示すデータが諸元計測用特徴点リスト24に記録される。諸元計測用特徴点リスト24は、適宜の記憶手段(例えば、図2の外部記憶装置5)に記録される。諸元計測用特徴点リスト24は、画像に移動領域が出現する度に各移動領域について生成される。
Referring to FIG. 3A again, when the feature measurement feature points are detected and tracked in step S07, the feature measurement feature points are detected and tracked, that is, the various features in the frame image at each time are detected. Data indicating the position of the original measurement feature point is recorded in the specification measurement feature point list 24. The feature measurement feature point list 24 is recorded in an appropriate storage means (for example, the external storage device 5 in FIG. 2). The feature measurement feature point list 24 is generated for each moving region every time the moving region appears in the image.
3.諸元計測用特徴点に基づく車両の諸元の算出
諸元計測用特徴点の検出と追尾の処理が行われた後、その諸元計測用特徴点を用いて車両の諸元が算出される。より具体的には、図3Bに示されているように、まず、各車両の全体が各フレーム画像に規定された特定の処理エリアに進入した時点が検出され(ステップS08)、更に、該処理エリアから該車両全体が退出した時点が検出される(ステップS09)。図12は、車両の処理エリアへの進入と退出の検出について概念的に示した図である。各フレーム画像の特定の領域(例えば、フレーム画像の下部に規定された領域)が、処理エリア44として規定され、各車両に対応する移動領域の全体が、処理エリア44に進入した時点、及び、処理エリア44から退出した時点が検出される。 3. Calculation of vehicle specifications based on feature measurement feature points After the feature measurement feature points are detected and tracked, the vehicle specification is calculated using the feature measurement feature points. . More specifically, as shown in FIG. 3B, first, a point in time when each vehicle has entered a specific processing area defined in each frame image is detected (step S08). A point in time when the entire vehicle leaves the area is detected (step S09). FIG. 12 is a diagram conceptually illustrating the detection of entry and exit of the processing area of the vehicle. A specific area of each frame image (for example, an area defined at the bottom of the frame image) is defined as theprocessing area 44, and when the entire moving area corresponding to each vehicle enters the processing area 44, and A time point when the user leaves the processing area 44 is detected.
諸元計測用特徴点の検出と追尾の処理が行われた後、その諸元計測用特徴点を用いて車両の諸元が算出される。より具体的には、図3Bに示されているように、まず、各車両の全体が各フレーム画像に規定された特定の処理エリアに進入した時点が検出され(ステップS08)、更に、該処理エリアから該車両全体が退出した時点が検出される(ステップS09)。図12は、車両の処理エリアへの進入と退出の検出について概念的に示した図である。各フレーム画像の特定の領域(例えば、フレーム画像の下部に規定された領域)が、処理エリア44として規定され、各車両に対応する移動領域の全体が、処理エリア44に進入した時点、及び、処理エリア44から退出した時点が検出される。 3. Calculation of vehicle specifications based on feature measurement feature points After the feature measurement feature points are detected and tracked, the vehicle specification is calculated using the feature measurement feature points. . More specifically, as shown in FIG. 3B, first, a point in time when each vehicle has entered a specific processing area defined in each frame image is detected (step S08). A point in time when the entire vehicle leaves the area is detected (step S09). FIG. 12 is a diagram conceptually illustrating the detection of entry and exit of the processing area of the vehicle. A specific area of each frame image (for example, an area defined at the bottom of the frame image) is defined as the
更に、諸元計測用特徴点リスト24に記録されている各移動領域(即ち、各車両)の諸元計測用特徴点の履歴データのうち、各車両の全体が処理エリア44に進入した時点と処理エリア44から退出した時点の間の時間についての履歴データを用いて、車両の諸元を示す車両諸元データ22が算出される(ステップS13)。車両諸元データ22の算出は、各車両の全体が処理エリア44に進入した時点と処理エリア44から退出した時点の間の時間の各時刻における、フレーム画像における諸元計測用特徴点の位置のデータに対してモーションステレオ処理が行われることによって行われる。モーションステレオ処理により、各時刻における諸元計測用特徴点の3次元座標(厳密には、車両と共に移動する3次元座標における3次元座標)が計算され、その3次元座標から車両の諸元が得られる。
Further, among the history data of the feature measurement feature points of each moving area (that is, each vehicle) recorded in the feature measurement feature point list 24, the time when the entire vehicle enters the processing area 44, and The vehicle specification data 22 indicating the specification of the vehicle is calculated using the history data about the time between the time of exiting the processing area 44 (step S13). The calculation of the vehicle specification data 22 is performed by calculating the position of the feature measurement feature point in the frame image at each time between the time when the entire vehicle enters the processing area 44 and the time when the vehicle leaves the processing area 44. This is done by performing motion stereo processing on the data. The motion stereo processing calculates the three-dimensional coordinates of the feature measurement feature points at each time (strictly speaking, the three-dimensional coordinates of the three-dimensional coordinates that move with the vehicle), and obtains the vehicle specifications from the three-dimensional coordinates. It is done.
図13A、図13Bは、本実施形態における、各諸元計測用特徴点の3次元座標を求めるためのモーションステレオ処理を説明する概念図である。図13Aを参照して、本実施形態におけるモーションステレオ処理では、車両の下面33にある諸元計測用特徴点#3のフレーム画像における移動量から、実空間内における車両の移動量dCが算出される。実空間路面上にある点のフレーム画像における移動量と、当該点の実空間における移動量との対応関係は、カメラ1の空間的配置に基づいて事前に得ることができる。この事実を利用して、車両の下面33にある諸元計測用特徴点#3(これは、実空間において路面上にある点と近似できる)のフレーム画像における移動量から、諸元計測用特徴点#3の実空間における移動量dCを算出することができる。
13A and 13B are conceptual diagrams illustrating motion stereo processing for obtaining the three-dimensional coordinates of each feature measurement feature point in the present embodiment. With reference to FIG. 13A, in the motion stereo processing in the present embodiment, the moving amount d C of the vehicle in the real space is calculated from the moving amount in the frame image of the feature measurement feature point # 3 on the lower surface 33 of the vehicle. Is done. The correspondence between the movement amount of the point on the real space road surface in the frame image and the movement amount of the point in the real space can be obtained in advance based on the spatial arrangement of the camera 1. Using this fact, the feature measurement feature point # 3 on the lower surface 33 of the vehicle can be approximated from the amount of movement in the frame image of the feature point # 3 (which can be approximated to a point on the road surface in real space). The amount of movement d C of the point # 3 in the real space can be calculated.
図13Bに図示されているように、モーションステレオ処理は、諸元計測用特徴点#1、~#6が、算出された移動量dCだけ移動しているという前提に基づいて行われる。即ち、諸元計測用特徴点#1~#6の3次元座標は、諸元計測用特徴点#1~#6が移動量dCだけ移動しているとして行われたモーションステレオ処理により算出される。
As illustrated in FIG. 13B, the motion stereo process is performed based on the premise that the feature measurement feature points # 1 to # 6 are moved by the calculated movement amount d C. That is, three-dimensional coordinates of the specification for measurement feature points # 1 to # 6 are calculated by the motion stereo process performed as specifications for measurement feature points # 1 to # 6 are moved by the movement amount d C The
各諸元計測用特徴点の3次元座標が算出されると、その3次元座標を用いて車両の諸元即ち、車両の幅、長さ、高さが算出される。車両の幅は、図1Aに示されているように、側面31、32にある諸元計測用特徴点#1、#2の3次元座標から算出される。また、図1Bに示されているように、車両の長さは、前面34及び後面35にある諸元計測用特徴点#4、#5の3次元座標から算出される。更に、図1Cに示されているように、車両の高さは、下面33及び上面36にある諸元計測用特徴点#3、#6の3次元座標から算出される。
When the three-dimensional coordinates of each feature measurement feature point are calculated, the vehicle specifications, that is, the width, length, and height of the vehicle are calculated using the three-dimensional coordinates. The width of the vehicle is calculated from the three-dimensional coordinates of the feature measurement feature points # 1 and # 2 on the side surfaces 31 and 32, as shown in FIG. 1A. Also, as shown in FIG. 1B, the length of the vehicle is calculated from the three-dimensional coordinates of the feature measurement feature points # 4 and # 5 on the front surface 34 and the rear surface 35. Further, as shown in FIG. 1C, the height of the vehicle is calculated from the three-dimensional coordinates of the feature measurement feature points # 3 and # 6 on the lower surface 33 and the upper surface.
更に、図3Bに示されているように、算出された車両の諸元を示す車両諸元データ22が生成される。車両諸元データ22は、外部記憶装置5に記憶される。その後、算出された車両の諸元が適宜の出力装置(例えば、表示装置)を用いて出力され(ステップS11)、諸元が算出された車両に対応する諸元計測用特徴点リスト24が削除される(ステップS12)。以上で、車両の諸元を算出するための処理が完了する。
Further, as shown in FIG. 3B, vehicle specification data 22 indicating the calculated vehicle specifications is generated. The vehicle specification data 22 is stored in the external storage device 5. Thereafter, the calculated vehicle specifications are output using an appropriate output device (for example, a display device) (step S11), and the feature measurement feature point list 24 corresponding to the vehicle for which the specifications are calculated is deleted. (Step S12). This completes the process for calculating the vehicle specifications.
以上に説明されているように、本実施形態では、車両の各面について諸元計測用特徴点が抽出され、その諸元計測用特徴点に対してモーションステレオ処理を行うことで各諸元計測用特徴点の3次元座標が算出される。算出された各諸元計測用特徴点の3次元座標から、車両の諸元(幅、長さ、高さ)が算出される。ここで、本実施形態における車両の諸元の計測処理では、車両の各面において抽出される諸元計測用特徴点の位置について一定の自由度があり、よって、ロバストな画像処理によって諸元計測用特徴点を検出可能である。このように、本実施形態における車両の諸元の計測処理によれば、ロバストな画像処理によって車両の諸元(例えば、幅、長さ、高さ)を算出することができる。
As described above, in this embodiment, feature measurement feature points are extracted for each surface of the vehicle, and each feature measurement is performed by performing motion stereo processing on the feature measurement feature points. The three-dimensional coordinates of the feature points for use are calculated. The vehicle specifications (width, length, height) are calculated from the calculated three-dimensional coordinates of each feature measurement feature point. Here, in the measurement processing of the vehicle specifications in the present embodiment, there is a certain degree of freedom with respect to the position of the feature measurement feature points extracted on each surface of the vehicle, and therefore the specification measurement is performed by robust image processing. Feature points can be detected. Thus, according to the measurement processing of the vehicle specifications in the present embodiment, the vehicle specifications (for example, width, length, height) can be calculated by robust image processing.
以上には、本発明の実施形態が具体的に記述されているが、本発明は、上記の実施形態には限定されない。本発明が、様々な変更と共に実施され得ることは、当業者には自明的であろう。例えば、上記には、車両の幅、長さ、高さの全てが算出される実施形態が記述されているが、車両の幅、長さ、高さの全てが算出されなくてもよい。本発明は、車両の幅、長さ、高さのうちの少なくとも一つを算出する場合に適用可能である。この場合、諸元計測用特徴点#1~#6のうちの必要があるもののみが検出されてもよい。
Although the embodiment of the present invention has been specifically described above, the present invention is not limited to the above embodiment. It will be apparent to those skilled in the art that the present invention may be practiced with various modifications. For example, in the above description, an embodiment in which all of the width, length, and height of the vehicle are calculated is described. However, all of the width, length, and height of the vehicle need not be calculated. The present invention is applicable when calculating at least one of the width, length, and height of a vehicle. In this case, only necessary ones of feature measurement feature points # 1 to # 6 may be detected.
Claims (20)
- 車両を逐次に撮影して前記車両のフレーム画像を取得する撮影装置と、
前記フレーム画像に基づいて前記車両の幅を算出する画像処理装置
とを具備し、
前記画像処理装置は、
前記フレーム画像のうちの少なくとも一について、前記車両の形状を近似する直方体の第1面にある特徴点である第1諸元計測用特徴点と、前記直方体の第2面にある特徴点である第2諸元計測用特徴点と、前記直方体の第3面にある特徴点である第3諸元計測用特徴点とを検出する特徴点検出手段と、
前記第1諸元計測用特徴点、前記第2諸元計測用特徴点及び前記第3諸元計測用特徴点に基づいて前記車両の幅を算出する車両諸元算出手段
とを備え、
前記第1面は、前記車両の第1側面に対応する前記直方体の面であり、
前記第2面は、前記車両の第2側面に対応する前記直方体の面であり、
前記第3面は、前記車両の下面に対応する前記直方体の面であり、
前記車両諸元算出手段は、前記第3諸元計測用特徴点の移動量から前記車両の移動量を算出し、前記車両の移動量を用いて前記第1諸元計測用特徴点及び前記第2諸元計測用特徴点に対してモーションステレオ処理を行うことによって前記第1諸元計測用特徴点及び前記第2諸元計測用特徴点の3次元座標を算出し、算出された前記第1諸元計測用特徴点及び前記第2諸元計測用特徴点の3次元座標から前記車両の幅を算出し、
前記特徴点検出手段によって検出される前記第1諸元計測用特徴点の位置は、前記第1面の面内において自由度があり、
前記特徴点検出手段によって検出される前記第2諸元計測用特徴点の位置は、前記第2面の面内において自由度があり、
前記特徴点検出手段によって検出される前記第3諸元計測用特徴点の位置は、前記第3面の面内において自由度がある
車両諸元計測装置。 A photographing device for sequentially photographing the vehicle to obtain a frame image of the vehicle;
An image processing device that calculates the width of the vehicle based on the frame image,
The image processing apparatus includes:
At least one of the frame images is a first feature measurement feature point that is a feature point on a first surface of a cuboid that approximates the shape of the vehicle, and a feature point that is on a second surface of the cuboid. Feature point detection means for detecting a second feature measurement feature point and a third feature measurement feature point that is a feature point on the third surface of the rectangular parallelepiped;
Vehicle feature calculation means for calculating the width of the vehicle based on the first feature measurement feature point, the second feature measurement feature point, and the third feature measurement feature point;
The first surface is a surface of the rectangular parallelepiped corresponding to the first side surface of the vehicle,
The second surface is a surface of the rectangular parallelepiped corresponding to the second side surface of the vehicle,
The third surface is a surface of the rectangular parallelepiped corresponding to the lower surface of the vehicle,
The vehicle specification calculation means calculates a movement amount of the vehicle from a movement amount of the third feature measurement feature point, and uses the movement amount of the vehicle to calculate the first feature measurement feature point and the first feature value. Two-dimensional measurement feature points are subjected to motion stereo processing to calculate three-dimensional coordinates of the first feature measurement feature points and the second feature measurement feature points, and the calculated first feature points The width of the vehicle is calculated from the three-dimensional coordinates of the feature points for feature measurement and the feature points for second feature measurement,
The position of the first feature measurement feature point detected by the feature point detection means has a degree of freedom in the plane of the first surface,
The position of the second feature measurement feature point detected by the feature point detection means has a degree of freedom in the plane of the second surface,
The position of the third feature measurement feature point detected by the feature point detection means has a degree of freedom in the plane of the third surface. - 請求項1に記載の車両諸元計測装置であって、
前記特徴点検出手段が、前記フレーム画像から前記車両に対応する移動領域を抽出し、前記移動領域について、実空間において前記車両に接する線に対応している前記フレーム画像内の線である接線を抽出し、抽出された前記接線の交点のうち前記第1面にある交点を前記第1諸元計測用特徴点として決定するように構成された
車両諸元計測装置。 The vehicle specification measuring device according to claim 1,
The feature point detecting means extracts a moving area corresponding to the vehicle from the frame image, and for the moving area, a tangent that is a line in the frame image corresponding to a line in contact with the vehicle in a real space. A vehicle specification measurement device configured to determine an intersection on the first surface among the extracted intersections of the tangent lines as the first feature measurement feature point. - 請求項2に記載の車両諸元計測装置であって、
前記特徴点検出手段が、前記抽出された前記接線の交点のうち前記第2面にある交点を前記第2諸元計測用特徴点として決定するように構成された
車両諸元計測装置。 The vehicle specification measuring device according to claim 2,
The vehicle feature measuring apparatus configured to determine, as the second feature measuring feature point, the feature point detecting means that determines an intersection point on the second surface among the extracted intersection points of the tangent lines. - 請求項2又は3に記載の車両諸元計測装置であって、
前記特徴点検出手段が、抽出された前記接線の交点のうち前記第3面にある交点を前記第3諸元計測用特徴点として決定するように構成された
車両諸元計測装置。 The vehicle specification measuring device according to claim 2 or 3,
The vehicle feature measuring apparatus configured to determine, as the third feature measuring feature point, the feature point detecting means that determines an intersecting point on the third surface among the extracted intersections of the tangent lines. - 請求項1に記載の車両諸元計測装置であって、
前記特徴点検出手段が、前記フレーム画像から前記車両に対応する移動領域を抽出し、前記移動領域について、実空間において前記車両に接する線に対応している前記フレーム画像内の線である接線を抽出し、抽出された前記接線のうち前記第1面にある部分で構成された第1探索路に沿って特徴点を探索することにより前記第1諸元計測用特徴点を決定するように構成された
車両諸元計測装置。 The vehicle specification measuring device according to claim 1,
The feature point detecting means extracts a moving area corresponding to the vehicle from the frame image, and for the moving area, a tangent that is a line in the frame image corresponding to a line in contact with the vehicle in a real space. The first feature measurement feature point is determined by searching for a feature point along a first search path constituted by a portion of the extracted tangent line on the first surface of the extracted tangent line. Vehicle specification measuring device. - 請求項5に記載の車両諸元計測装置であって、
前記特徴点検出手段が、抽出された前記接線のうち前記第2面にある部分で構成された第2探索路に沿って特徴点を探索することにより前記第2諸元計測用特徴点を決定するように構成された
車両諸元計測装置。 The vehicle specification measuring device according to claim 5,
The feature point detecting means determines the second feature measurement feature point by searching for a feature point along a second search path constituted by a portion on the second surface of the extracted tangent line. A vehicle specification measuring device configured to be. - 請求項5又は6に記載の車両諸元計測装置であって、
前記特徴点検出手段が、抽出された前記接線のうち前記第3面にある部分で構成された第3探索路に沿って特徴点を探索することにより前記第3諸元計測用特徴点を決定するように構成された
車両諸元計測装置。 The vehicle specification measuring device according to claim 5 or 6,
The feature point detection means determines the third feature measurement feature point by searching for a feature point along a third search path constituted by a portion on the third surface of the extracted tangent line. A vehicle specification measuring device configured to be. - 請求項1に記載の車両諸元計測装置であって、
前記特徴点検出手段は、前記車両の第1側面に存在すると想定される部品の第1テンプレートと前記第1テンプレートにおける特徴点の位置を示す第1特徴点位置データとを含む第1テンプレートデータベースを有しており、
前記特徴点検出手段は、前記フレーム画像に対し前記第1テンプレートデータベースの前記テンプレートとのテンプレートマッチングにより最もマッチする前記第1テンプレートの位置である第1マッチング位置を求め、前記第1マッチング位置と前記第1特徴点位置データとから決定した位置に前記第1諸元計測用特徴点があるとして前記第1諸元計測用特徴点を検出するように構成された
車両諸元計測装置。 The vehicle specification measuring device according to claim 1,
The feature point detection means includes a first template database including a first template of a component assumed to be present on the first side surface of the vehicle and first feature point position data indicating a position of the feature point in the first template. Have
The feature point detection means obtains a first matching position that is a position of the first template that most closely matches the frame image by template matching with the template of the first template database, and the first matching position and the A vehicle specification measurement device configured to detect the first feature measurement feature point at the position determined from the first feature point position data, assuming that the feature specification feature point is present. - 請求項1又は8に記載の車両諸元計測装置であって、
前記特徴点検出手段は、前記車両の第2側面に存在すると想定される部品の第2テンプレートと前記第2テンプレートにおける特徴点の位置を示す第2特徴点位置データとを含む第2テンプレートデータベースを有しており、
前記特徴点検出手段は、前記フレーム画像に対し前記第2テンプレートデータベースの前記第2テンプレートとのテンプレートマッチングにより最もマッチする前記第2テンプレートの位置である第2マッチング位置を求め、前記第2マッチング位置と前記第2特徴点位置データとから決定した位置に前記第2諸元計測用特徴点があるとして前記第2諸元計測用特徴点を検出するように構成された
車両諸元計測装置。 The vehicle specification measuring device according to claim 1 or 8,
The feature point detection means includes a second template database including a second template of parts assumed to be present on the second side surface of the vehicle and second feature point position data indicating the position of the feature point in the second template. Have
The feature point detecting means obtains a second matching position that is a position of the second template that most closely matches the frame image by template matching with the second template of the second template database, and the second matching position. Vehicle feature measuring apparatus configured to detect the second feature measuring feature point at the position determined from the second feature point position data and the second feature measuring feature point. - 請求項8又は9に記載の車両諸元計測装置であって、
前記特徴点検出手段は、前記車両の下面に存在すると想定される部品の第3テンプレートと前記第3テンプレートにおける特徴点の位置を示す第3特徴点位置データとを含む第3テンプレートデータベースを有しており、
前記特徴点検出手段は、前記フレーム画像に対し前記第3テンプレートデータベースの前記第3テンプレートとのテンプレートマッチングにより最もマッチする前記第3テンプレートの位置である第3マッチング位置を求め、前記第3マッチング位置と前記第3特徴点位置データとから決定した位置に前記第3諸元計測用特徴点があるとして前記第3諸元計測用特徴点を検出するように構成された
車両諸元計測装置。 The vehicle specification measuring device according to claim 8 or 9, wherein
The feature point detection means includes a third template database including a third template of a part assumed to exist on the lower surface of the vehicle and third feature point position data indicating the position of the feature point in the third template. And
The feature point detection means obtains a third matching position that is a position of the third template that most matches the frame image by template matching with the third template of the third template database, and the third matching position And the third feature point position data. The vehicle feature measurement device is configured to detect the third feature measurement feature point at a position determined from the third feature point position data. - 請求項1に記載の車両諸元計測装置であって、
前記特徴点検出手段は、前記フレーム画像について、前記直方体の第4面にある特徴点である第4諸元計測用特徴点と、前記直方体の第5面にある特徴点である第5諸元計測用特徴点とを検出し、
前記第4面は、前記車両の前面に対応する前記直方体の面であり、
前記第5面は、前記車両の後面に対応する前記直方体の面であり、
前記車両諸元算出手段は、前記車両の移動量を用いて前記第4諸元計測用特徴点及び前記第5諸元計測用特徴点に対してモーションステレオ処理を行うことによって前記第4諸元計測用特徴点及び前記第5諸元計測用特徴点の3次元座標を算出し、算出された前記第4諸元計測用特徴点及び前記第5諸元計測用特徴点の3次元座標から前記車両の長さを算出し、
前記特徴点検出手段によって検出される前記第4諸元計測用特徴点の位置は、前記第4面の面内において自由度があり、
前記特徴点検出手段によって検出される前記第5諸元計測用特徴点の位置は、前記第5面の面内において自由度がある
車両諸元計測装置。 The vehicle specification measuring device according to claim 1,
The feature point detection means includes, for the frame image, fourth feature measurement feature points that are feature points on the fourth surface of the rectangular parallelepiped and fifth feature points that are feature points on the fifth surface of the rectangular parallelepiped. Detect feature points for measurement,
The fourth surface is a surface of the rectangular parallelepiped corresponding to the front surface of the vehicle,
The fifth surface is a surface of the rectangular parallelepiped corresponding to the rear surface of the vehicle,
The vehicle specification calculation means performs motion stereo processing on the fourth feature measurement feature point and the fifth feature measurement feature point by using the amount of movement of the vehicle, thereby performing the fourth specification. The three-dimensional coordinates of the measurement feature point and the fifth feature measurement feature point are calculated, and the calculated third feature measurement feature point and the fifth feature measurement feature point are used to calculate the three-dimensional coordinates. Calculate the length of the vehicle,
The position of the fourth feature measurement feature point detected by the feature point detection means has a degree of freedom in the plane of the fourth surface,
The position of the fifth feature measurement feature point detected by the feature point detection means has a degree of freedom in the plane of the fifth surface. - 請求項1又は11に記載の車両諸元計測装置であって、
前記特徴点検出手段は、前記フレーム画像について、前記直方体の第6面にある特徴点である第6諸元計測用特徴点を検出し、
前記第6面は、前記車両の上面に対応する前記直方体の面であり、
前記車両諸元算出手段は、前記車両の移動量を用いて前記第3諸元計測用特徴点及び前記第6諸元計測用特徴点に対してモーションステレオ処理を行うことによって前記第3諸元計測用特徴点及び前記第6諸元計測用特徴点の3次元座標を算出し、算出された前記第3諸元計測用特徴点及び前記第6諸元計測用特徴点の3次元座標から前記車両の高さを算出し、
前記特徴点検出手段によって検出される前記第6諸元計測用特徴点の位置は、前記第6面の面内において自由度がある
車両諸元計測装置。 The vehicle specification measuring device according to claim 1 or 11,
The feature point detecting means detects a feature point for measuring the sixth item, which is a feature point on the sixth surface of the rectangular parallelepiped, with respect to the frame image,
The sixth surface is a surface of the rectangular parallelepiped corresponding to the upper surface of the vehicle,
The vehicle specification calculation means performs the motion stereo processing on the third feature measurement feature point and the sixth feature measurement feature point using the movement amount of the vehicle, thereby performing the third feature measurement. The three-dimensional coordinates of the measurement feature point and the sixth feature measurement feature point are calculated, and the three-dimensional coordinates of the third feature measurement feature point and the sixth feature measurement feature point are calculated. Calculate the height of the vehicle,
The position of the sixth feature measurement feature point detected by the feature point detection means has a degree of freedom in the plane of the sixth surface. - 車両を逐次に撮影して前記車両のフレーム画像を取得する撮影装置と、
前記フレーム画像に基づいて前記車両の長さを算出する画像処理装置
とを具備し、
前記画像処理装置は、
前記フレーム画像のうちの少なくとも一について、前記車両の形状を近似する直方体の第3面にある特徴点である第3諸元計測用特徴点と、前記直方体の第4面にある特徴点である第4諸元計測用特徴点と、前記直方体の第5面にある特徴点である第5諸元計測用特徴点とを検出する特徴点検出手段と、
前記第3諸元計測用特徴点、前記第4諸元計測用特徴点及び前記第5諸元計測用特徴点に基づいて前記車両の長さを算出する車両諸元算出手段
とを備え、
前記第3面は、前記車両の下面に対応する前記直方体の面であり、
前記第4面は、前記車両の前面に対応する前記直方体の面であり、
前記第5面は、前記車両の後面に対応する前記直方体の面であり、
前記車両諸元算出手段は、前記第3諸元計測用特徴点の移動量から前記車両の移動量を算出し、前記車両の移動量を用いて前記第4諸元計測用特徴点及び前記第5諸元計測用特徴点に対してモーションステレオ処理を行うことによって前記第4諸元計測用特徴点及び前記第5諸元計測用特徴点の3次元座標を算出し、算出された前記第4諸元計測用特徴点及び前記第5諸元計測用特徴点の3次元座標から前記車両の長さを算出し、
前記特徴点検出手段によって検出される前記第3諸元計測用特徴点の位置は、前記第3面の面内において自由度があり、
前記特徴点検出手段によって検出される前記第4諸元計測用特徴点の位置は、前記第4面の面内において自由度があり、
前記特徴点検出手段によって検出される前記第5諸元計測用特徴点の位置は、前記第5面の面内において自由度がある
車両諸元計測装置。 A photographing device for sequentially photographing the vehicle to obtain a frame image of the vehicle;
An image processing device that calculates the length of the vehicle based on the frame image;
The image processing apparatus includes:
At least one of the frame images is a third feature measurement feature point that is a feature point on a third surface of a rectangular parallelepiped that approximates the shape of the vehicle, and a feature point that is on a fourth surface of the rectangular parallelepiped. Feature point detecting means for detecting a fourth feature measurement feature point and a fifth feature measurement feature point that is a feature point on the fifth surface of the rectangular parallelepiped;
Vehicle feature calculation means for calculating the length of the vehicle based on the third feature measurement feature point, the fourth feature measurement feature point, and the fifth feature measurement feature point;
The third surface is a surface of the rectangular parallelepiped corresponding to the lower surface of the vehicle,
The fourth surface is a surface of the rectangular parallelepiped corresponding to the front surface of the vehicle,
The fifth surface is a surface of the rectangular parallelepiped corresponding to the rear surface of the vehicle,
The vehicle specification calculation means calculates a movement amount of the vehicle from a movement amount of the third feature measurement feature point, and uses the movement amount of the vehicle to calculate the fourth feature measurement feature point and the first feature point. Three-dimensional coordinates of the fourth feature measurement feature point and the fifth feature measurement feature point are calculated by performing motion stereo processing on the feature specification feature point for five specifications, and the calculated fourth feature point is calculated. Calculating the length of the vehicle from the three-dimensional coordinates of the feature measurement feature points and the fifth feature measurement feature points;
The position of the third feature measurement feature point detected by the feature point detection means has a degree of freedom in the plane of the third surface,
The position of the fourth feature measurement feature point detected by the feature point detection means has a degree of freedom in the plane of the fourth surface,
The position of the fifth feature measurement feature point detected by the feature point detection means has a degree of freedom in the plane of the fifth surface. - 車両を逐次に撮影して前記車両のフレーム画像を取得する撮影装置と、
前記フレーム画像に基づいて前記車両の高さを算出する画像処理装置
とを具備し、
前記画像処理装置は、
前記フレーム画像のうちの少なくとも一について、前記車両の形状を近似する直方体の第3面にある特徴点である第3諸元計測用特徴点と、前記直方体の第6面にある特徴点である第6諸元計測用特徴点とを検出する特徴点検出手段と、
前記第3諸元計測用特徴点及び前記第6諸元計測用特徴点に基づいて前記車両の高さを算出する車両諸元算出手段
とを備え、
前記第3面は、前記車両の下面に対応する前記直方体の面であり、
前記第6面は、前記車両の上面に対応する前記直方体の面であり、
前記車両諸元算出手段は、前記第3諸元計測用特徴点の移動量から前記車両の移動量を算出し、前記車両の移動量を用いて前記第3諸元計測用特徴点及び前記第6諸元計測用特徴点に対してモーションステレオ処理を行うことによって前記第3諸元計測用特徴点及び前記第6諸元計測用特徴点の3次元座標を算出し、算出された前記第3諸元計測用特徴点及び前記第6諸元計測用特徴点の3次元座標から前記車両の高さを算出し、
前記特徴点検出手段によって検出される前記第3諸元計測用特徴点の位置は、前記第3面の面内において自由度があり、
前記特徴点検出手段によって検出される前記第6諸元計測用特徴点の位置は、前記第6面の面内において自由度がある
車両諸元計測装置。 A photographing device for sequentially photographing the vehicle to obtain a frame image of the vehicle;
An image processing device that calculates the height of the vehicle based on the frame image,
The image processing apparatus includes:
At least one of the frame images is a third feature measurement feature point that is a feature point on the third surface of the rectangular parallelepiped that approximates the shape of the vehicle, and a feature point that is on the sixth surface of the rectangular parallelepiped. A feature point detecting means for detecting a feature point for sixth specification measurement;
Vehicle feature calculation means for calculating the height of the vehicle based on the third feature measurement feature point and the sixth feature measurement feature point;
The third surface is a surface of the rectangular parallelepiped corresponding to the lower surface of the vehicle,
The sixth surface is a surface of the rectangular parallelepiped corresponding to the upper surface of the vehicle,
The vehicle specification calculation means calculates a movement amount of the vehicle from a movement amount of the third feature measurement feature point, and uses the movement amount of the vehicle to calculate the third feature measurement feature point and the first feature point. Three-dimensional coordinates of the third feature measurement feature point and the sixth feature measurement feature point are calculated by performing motion stereo processing on the feature specification feature point, and the calculated third feature point is calculated. Calculating the height of the vehicle from the three-dimensional coordinates of the feature points for feature measurement and the feature points for feature specification 6.
The position of the third feature measurement feature point detected by the feature point detection means has a degree of freedom in the plane of the third surface,
The position of the sixth feature measurement feature point detected by the feature point detection means has a degree of freedom in the plane of the sixth surface. - 車両を逐次に撮影して前記車両のフレーム画像を取得するステップと、
前記フレーム画像について、前記車両の形状を近似する直方体の第1面にある特徴点である第1諸元計測用特徴点と、前記直方体の第2面にある特徴点である第2諸元計測用特徴点と、前記直方体の第3面にある特徴点である第3諸元計測用特徴点とを検出するステップと、
前記第1諸元計測用特徴点、前記第2諸元計測用特徴点及び前記第3諸元計測用特徴点に基づいて前記車両の幅を算出するステップ
とを具備し、
前記第1面は、前記車両の第1側面に対応する前記直方体の面であり、
前記第2面は、前記車両の第2側面に対応する前記直方体の面であり、
前記第3面は、前記車両の下面に対応する前記直方体の面であり、
前記車両の幅を算出するステップは、
前記第3諸元計測用特徴点の移動量から前記車両の移動量を算出するステップと、
前記車両の移動量を用いて前記第1諸元計測用特徴点及び前記第2諸元計測用特徴点に対してモーションステレオ処理を行うことによって前記第1諸元計測用特徴点及び前記第2諸元計測用特徴点の3次元座標を算出するステップと、
算出された前記第1諸元計測用特徴点及び前記第2諸元計測用特徴点の3次元座標から前記車両の幅を算出するステップ
とを含み、
前記検出するステップにおいて検出される前記第1諸元計測用特徴点の位置は、前記第1面の面内において自由度があり、
前記検出するステップにおいて検出される前記第2諸元計測用特徴点の位置は、前記第2面の面内において自由度があり、
前記検出するステップにおいて検出される前記第3諸元計測用特徴点の位置は、前記第3面の面内において自由度がある
車両諸元計測方法。 Capturing the vehicle sequentially to obtain a frame image of the vehicle;
For the frame image, a first feature measurement feature point that is a feature point on a first surface of a rectangular parallelepiped approximating the shape of the vehicle, and a second feature measurement that is a feature point on a second surface of the rectangular parallelepiped. Detecting a feature point for use and a feature point for measuring the third specification which is a feature point on the third surface of the rectangular parallelepiped;
Calculating the width of the vehicle based on the first feature measurement feature point, the second feature measurement feature point, and the third feature measurement feature point;
The first surface is a surface of the rectangular parallelepiped corresponding to the first side surface of the vehicle,
The second surface is a surface of the rectangular parallelepiped corresponding to the second side surface of the vehicle,
The third surface is a surface of the rectangular parallelepiped corresponding to the lower surface of the vehicle,
The step of calculating the width of the vehicle includes:
Calculating the amount of movement of the vehicle from the amount of movement of the third feature measurement feature point;
By performing motion stereo processing on the first feature measurement feature point and the second feature measurement feature point using the amount of movement of the vehicle, the first feature measurement feature point and the second feature measurement point. Calculating three-dimensional coordinates of feature measurement feature points;
Calculating the width of the vehicle from the calculated three-dimensional coordinates of the first feature measurement feature points and the second feature measurement feature points;
The position of the first feature measurement feature point detected in the detecting step has a degree of freedom in the plane of the first surface,
The position of the second feature measurement feature point detected in the detecting step has a degree of freedom in the plane of the second surface,
The vehicle specification measurement method, wherein the position of the third feature measurement feature point detected in the detection step has a degree of freedom in the plane of the third surface. - 車両を逐次に撮影して前記車両のフレーム画像を取得するステップと、
前記フレーム画像のうちの少なくとも一について、前記車両の形状を近似する直方体の第3面にある特徴点である第3諸元計測用特徴点と、前記直方体の第4面にある特徴点である第4諸元計測用特徴点と、前記直方体の第5面にある特徴点である第5諸元計測用特徴点とを検出するステップと、
前記第3諸元計測用特徴点、前記第4諸元計測用特徴点及び前記第5諸元計測用特徴点に基づいて前記車両の長さを算出するステップ
とを具備し、
前記第3面は、前記車両の下面に対応する前記直方体の面であり、
前記第4面は、前記車両の前面に対応する前記直方体の面であり、
前記第5面は、前記車両の後面に対応する前記直方体の面であり、
前記車両の長さを算出するステップは、
前記第3諸元計測用特徴点の移動量から前記車両の移動量を算出するステップと、
前記車両の移動量を用いて前記第4諸元計測用特徴点及び前記第5諸元計測用特徴点に対してモーションステレオ処理を行うことによって前記第4諸元計測用特徴点及び前記第5諸元計測用特徴点の3次元座標を算出するステップと、
算出された前記第4諸元計測用特徴点及び前記第5諸元計測用特徴点の3次元座標から前記車両の長さを算出するステップ
とを含み、
前記検出するステップにおいて検出される前記第3諸元計測用特徴点の位置は、前記第3面の面内において自由度があり、
前記検出するステップにおいて検出される前記第4諸元計測用特徴点の位置は、前記第4面の面内において自由度があり、
前記検出するステップにおいて検出される前記第5諸元計測用特徴点の位置は、前記第5面の面内において自由度がある
車両諸元計測方法。 Capturing the vehicle sequentially to obtain a frame image of the vehicle;
At least one of the frame images is a third feature measurement feature point that is a feature point on a third surface of a rectangular parallelepiped that approximates the shape of the vehicle, and a feature point that is on a fourth surface of the rectangular parallelepiped. Detecting a fourth feature measurement feature point and a fifth feature measurement feature point that is a feature point on the fifth surface of the rectangular parallelepiped;
Calculating the length of the vehicle based on the third feature measurement feature point, the fourth feature measurement feature point, and the fifth feature measurement feature point;
The third surface is a surface of the rectangular parallelepiped corresponding to the lower surface of the vehicle,
The fourth surface is a surface of the rectangular parallelepiped corresponding to the front surface of the vehicle,
The fifth surface is a surface of the rectangular parallelepiped corresponding to the rear surface of the vehicle,
The step of calculating the length of the vehicle includes
Calculating the amount of movement of the vehicle from the amount of movement of the third feature measurement feature point;
By performing motion stereo processing on the fourth feature measurement feature point and the fifth feature measurement feature point using the movement amount of the vehicle, the fourth feature measurement feature point and the fifth feature point. Calculating three-dimensional coordinates of feature measurement feature points;
Calculating the length of the vehicle from the calculated three-dimensional coordinates of the fourth feature measurement feature point and the fifth feature measurement feature point;
The position of the third feature measurement feature point detected in the detecting step has a degree of freedom in the plane of the third surface,
The position of the fourth feature measurement feature point detected in the detecting step has a degree of freedom in the plane of the fourth surface,
The vehicle specification measurement method, wherein the position of the fifth feature measurement feature point detected in the detecting step has a degree of freedom in the plane of the fifth surface. - 車両を逐次に撮影して前記車両のフレーム画像を取得するステップと、
前記フレーム画像のうちの少なくとも一について、前記車両の形状を近似する直方体の第3面にある特徴点である第3諸元計測用特徴点と、前記直方体の第6面にある特徴点である第6諸元計測用特徴点とを検出するステップと、
前記第3諸元計測用特徴点及び前記第6諸元計測用特徴点に基づいて前記車両の高さを算出するステップ
とを具備し、
前記第3面は、前記車両の下面に対応する前記直方体の面であり、
前記第6面は、前記車両の上面に対応する前記直方体の面であり、
前記車両の高さを算出するステップは、
前記第3諸元計測用特徴点の移動量から前記車両の移動量を算出するステップと、
前記車両の移動量を用いて前記第3諸元計測用特徴点及び前記第6諸元計測用特徴点に対してモーションステレオ処理を行うことによって前記第3諸元計測用特徴点及び前記第6諸元計測用特徴点の3次元座標を算出するステップと、
算出された前記第3諸元計測用特徴点及び前記第6諸元計測用特徴点の3次元座標から前記車両の高さを算出するステップ
とを含み、
前記検出するステップにおいて検出される前記第3諸元計測用特徴点の位置は、前記第3面の面内において自由度があり、
前記検出するステップにおいて検出される前記第6諸元計測用特徴点の位置は、前記第6面の面内において自由度がある
車両諸元計測方法。 Capturing the vehicle sequentially to obtain a frame image of the vehicle;
At least one of the frame images is a third feature measurement feature point that is a feature point on the third surface of the rectangular parallelepiped that approximates the shape of the vehicle, and a feature point that is on the sixth surface of the rectangular parallelepiped. Detecting a sixth feature measurement feature point;
Calculating the height of the vehicle based on the third feature measurement feature point and the sixth feature measurement feature point,
The third surface is a surface of the rectangular parallelepiped corresponding to the lower surface of the vehicle,
The sixth surface is a surface of the rectangular parallelepiped corresponding to the upper surface of the vehicle,
The step of calculating the height of the vehicle includes
Calculating the amount of movement of the vehicle from the amount of movement of the third feature measurement feature point;
By performing motion stereo processing on the third feature measurement feature point and the sixth feature measurement feature point using the movement amount of the vehicle, the third feature measurement feature point and the sixth feature point. Calculating three-dimensional coordinates of feature measurement feature points;
Calculating the height of the vehicle from the calculated three-dimensional measurement feature points and the sixth feature measurement feature points;
The position of the third feature measurement feature point detected in the detecting step has a degree of freedom in the plane of the third surface,
The vehicle specification measurement method, wherein the position of the sixth feature measurement feature point detected in the detection step has a degree of freedom in the plane of the sixth surface. - プログラムを格納した記録媒体であって、
前記プログラムを実行したとき、前記プログラムは、演算装置に、下記ステップ:
車両を逐次に撮影してすることで得られた前記車両のフレーム画像について、前記車両の形状を近似する直方体の第1面にある特徴点である第1諸元計測用特徴点と、前記直方体の第2面にある特徴点である第2諸元計測用特徴点と、前記直方体の第3面にある特徴点である第3諸元計測用特徴点とを検出するステップ、及び、
前記第1諸元計測用特徴点、前記第2諸元計測用特徴点及び前記第3諸元計測用特徴点に基づいて前記車両の幅を算出するステップ
を実行させ、
前記第1面は、前記車両の第1側面に対応する前記直方体の面であり、
前記第2面は、前記車両の第2側面に対応する前記直方体の面であり、
前記第3面は、前記車両の下面に対応する前記直方体の面であり、
前記車両の幅を算出するステップは、
前記第3諸元計測用特徴点の移動量から前記車両の移動量を算出するステップと、
前記車両の移動量を用いて前記第1諸元計測用特徴点及び前記第2諸元計測用特徴点に対してモーションステレオ処理を行うことによって前記第1諸元計測用特徴点及び前記第2諸元計測用特徴点の3次元座標を算出するステップと、
算出された前記第1諸元計測用特徴点及び前記第2諸元計測用特徴点の3次元座標から前記車両の幅を算出するステップ
とを含み、
前記検出するステップにおいて検出される前記第1諸元計測用特徴点の位置は、前記第1面の面内において自由度があり、
前記検出するステップにおいて検出される前記第2諸元計測用特徴点の位置は、前記第2面の面内において自由度があり、
前記検出するステップにおいて検出される前記第3諸元計測用特徴点の位置は、前記第3面の面内において自由度がある
記録媒体。 A recording medium storing a program,
When the program is executed, the program causes the computing device to perform the following steps:
A feature point for first specification measurement that is a feature point on a first surface of a rectangular parallelepiped that approximates the shape of the vehicle, and the rectangular parallelepiped for a frame image of the vehicle obtained by sequentially photographing the vehicle Detecting a second feature measurement feature point that is a feature point on the second surface and a third feature measurement feature point that is a feature point on the third surface of the rectangular parallelepiped; and
Calculating a width of the vehicle based on the first feature measurement feature point, the second feature measurement feature point, and the third feature measurement feature point;
The first surface is a surface of the rectangular parallelepiped corresponding to the first side surface of the vehicle,
The second surface is a surface of the rectangular parallelepiped corresponding to the second side surface of the vehicle,
The third surface is a surface of the rectangular parallelepiped corresponding to the lower surface of the vehicle,
The step of calculating the width of the vehicle includes:
Calculating the amount of movement of the vehicle from the amount of movement of the third feature measurement feature point;
By performing motion stereo processing on the first feature measurement feature point and the second feature measurement feature point using the amount of movement of the vehicle, the first feature measurement feature point and the second feature measurement point. Calculating three-dimensional coordinates of feature measurement feature points;
Calculating the width of the vehicle from the calculated three-dimensional coordinates of the first feature measurement feature points and the second feature measurement feature points;
The position of the first feature measurement feature point detected in the detecting step has a degree of freedom in the plane of the first surface,
The position of the second feature measurement feature point detected in the detecting step has a degree of freedom in the plane of the second surface,
The position of the third feature measurement feature point detected in the detecting step has a degree of freedom in the plane of the third surface. - プログラムを格納した記録媒体であって、
前記プログラムを実行したとき、前記プログラムは、演算装置に、下記ステップ:
車両を逐次に撮影して前記車両のフレーム画像を取得するステップと、
前記フレーム画像のうちの少なくとも一について、前記車両の形状を近似する直方体の第3面にある特徴点である第3諸元計測用特徴点と、前記直方体の第4面にある特徴点である第4諸元計測用特徴点と、前記直方体の第5面にある特徴点である第5諸元計測用特徴点とを検出するステップ、及び、
前記第3諸元計測用特徴点、前記第4諸元計測用特徴点及び前記第5諸元計測用特徴点に基づいて前記車両の長さを算出するステップ
を実行させ、
前記第3面は、前記車両の下面に対応する前記直方体の面であり、
前記第4面は、前記車両の前面に対応する前記直方体の面であり、
前記第5面は、前記車両の後面に対応する前記直方体の面であり、
前記車両の長さを算出するステップは、
前記第3諸元計測用特徴点の移動量から前記車両の移動量を算出するステップと、
前記車両の移動量を用いて前記第4諸元計測用特徴点及び前記第5諸元計測用特徴点に対してモーションステレオ処理を行うことによって前記第4諸元計測用特徴点及び前記第5諸元計測用特徴点の3次元座標を算出するステップと、
算出された前記第4諸元計測用特徴点及び前記第5諸元計測用特徴点の3次元座標から前記車両の長さを算出するステップ
とを含み、
前記検出するステップにおいて検出される前記第3諸元計測用特徴点の位置は、前記第3面の面内において自由度があり、
前記検出するステップにおいて検出される前記第4諸元計測用特徴点の位置は、前記第4面の面内において自由度があり、
前記検出するステップにおいて検出される前記第5諸元計測用特徴点の位置は、前記第5面の面内において自由度がある
記録媒体。 A recording medium storing a program,
When the program is executed, the program causes the computing device to perform the following steps:
Capturing the vehicle sequentially to obtain a frame image of the vehicle;
At least one of the frame images is a third feature measurement feature point that is a feature point on a third surface of a rectangular parallelepiped that approximates the shape of the vehicle, and a feature point that is on a fourth surface of the rectangular parallelepiped. Detecting a fourth feature measurement feature point and a fifth feature measurement feature point that is a feature point on the fifth surface of the rectangular parallelepiped; and
Calculating a length of the vehicle based on the third feature measurement feature point, the fourth feature measurement feature point, and the fifth feature measurement feature point;
The third surface is a surface of the rectangular parallelepiped corresponding to the lower surface of the vehicle,
The fourth surface is a surface of the rectangular parallelepiped corresponding to the front surface of the vehicle,
The fifth surface is a surface of the rectangular parallelepiped corresponding to the rear surface of the vehicle,
The step of calculating the length of the vehicle includes
Calculating the amount of movement of the vehicle from the amount of movement of the third feature measurement feature point;
By performing motion stereo processing on the fourth feature measurement feature point and the fifth feature measurement feature point using the movement amount of the vehicle, the fourth feature measurement feature point and the fifth feature point. Calculating three-dimensional coordinates of feature measurement feature points;
Calculating the length of the vehicle from the calculated three-dimensional coordinates of the fourth feature measurement feature point and the fifth feature measurement feature point;
The position of the third feature measurement feature point detected in the detecting step has a degree of freedom in the plane of the third surface,
The position of the fourth feature measurement feature point detected in the detecting step has a degree of freedom in the plane of the fourth surface,
The position of the fifth feature measurement feature point detected in the detecting step has a degree of freedom in the plane of the fifth surface. - プログラムを格納した記録媒体であって、
前記プログラムを実行したとき、前記プログラムは、演算装置に、下記ステップ:
車両を逐次に撮影して前記車両のフレーム画像を取得するステップと、
前記フレーム画像のうちの少なくとも一について、前記車両の形状を近似する直方体の第3面にある特徴点である第3諸元計測用特徴点と、前記直方体の第6面にある特徴点である第6諸元計測用特徴点とを検出するステップと、
前記第3諸元計測用特徴点及び前記第6諸元計測用特徴点に基づいて前記車両の高さを算出するステップ
とを具備し
前記第3面は、前記車両の下面に対応する前記直方体の面であり、
前記第6面は、前記車両の上面に対応する前記直方体の面であり、
前記車両の長さを算出するステップは、
前記第3諸元計測用特徴点の移動量から前記車両の移動量を算出するステップと、
前記車両の移動量を用いて前記第3諸元計測用特徴点及び前記第6諸元計測用特徴点に対してモーションステレオ処理を行うことによって前記第3諸元計測用特徴点及び前記第6諸元計測用特徴点の3次元座標を算出するステップと、
算出された前記第3諸元計測用特徴点及び前記第6諸元計測用特徴点の3次元座標から前記車両の高さを算出するステップ
とを含み、
前記検出するステップにおいて検出される前記第3諸元計測用特徴点の位置は、前記第3面の面内において自由度があり、
前記検出するステップにおいて検出される前記第6諸元計測用特徴点の位置は、前記第6面の面内において自由度がある
記録媒体。 A recording medium storing a program,
When the program is executed, the program causes the computing device to perform the following steps:
Capturing the vehicle sequentially to obtain a frame image of the vehicle;
At least one of the frame images is a third feature measurement feature point that is a feature point on the third surface of the rectangular parallelepiped that approximates the shape of the vehicle, and a feature point that is on the sixth surface of the rectangular parallelepiped. Detecting a sixth feature measurement feature point;
Calculating the height of the vehicle based on the third feature measurement feature point and the sixth feature measurement feature point, wherein the third surface corresponds to the lower surface of the vehicle. Of the
The sixth surface is a surface of the rectangular parallelepiped corresponding to the upper surface of the vehicle,
The step of calculating the length of the vehicle includes
Calculating the amount of movement of the vehicle from the amount of movement of the third feature measurement feature point;
By performing motion stereo processing on the third feature measurement feature point and the sixth feature measurement feature point using the movement amount of the vehicle, the third feature measurement feature point and the sixth feature point. Calculating three-dimensional coordinates of feature measurement feature points;
Calculating the height of the vehicle from the calculated three-dimensional measurement feature points and the sixth feature measurement feature points;
The position of the third feature measurement feature point detected in the detecting step has a degree of freedom in the plane of the third surface,
The position of the sixth feature measurement feature point detected in the detecting step has a degree of freedom in the plane of the sixth surface.
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