JP2013246009A - Object detection apparatus - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an object detection apparatus capable of properly recognizing an object shape regardless of the position of a detection target object.SOLUTION: An object detection apparatus 1 comprises an information acquisition device 2 which acquires a distance image Pi corresponding to a distance of each of segment regions set to a reference template, and an object detector 31a which generates a binarized image Mi by binarizing the distance image Pi with a binarization threshold value Dsh corresponding to a distance in a Z-axis direction and detects the shape of an object from the binarized image Mi. The object detector 31a varies the binarization threshold value Dsh in accordance with a change of the distance to the object defined as a detection target. Thus, even when the detection target object is positioned farther than the binarization threshold value Dsh, the shape of the object can be detected properly.

Description

  The present invention relates to an object detection apparatus that detects an object in a target area based on three-dimensional distance information.

  Conventionally, object detection devices using light have been developed in various fields. An object detection apparatus using a so-called distance image sensor can detect not only a planar image on a two-dimensional plane but also the shape and movement of the detection target object in the depth direction. In such an object detection apparatus, light in a predetermined wavelength band is projected from a laser light source or an LED (Light Emitting Diode) onto a target area, and the reflected light is received by a light receiving element such as a CMOS image sensor. Various types of distance image sensors are known.

  In a distance image sensor of a type that irradiates a target region with laser light having a predetermined dot pattern, reflected light from the target region of laser light having a dot pattern is received by a light receiving element. Then, based on the light receiving position of the dot on the light receiving element, the distance to each part of the detection target object (irradiation position of each dot on the detection target object) is detected using triangulation (for example, Patent Literature 1, Non-Patent Document 1).

JP 2012-32379 A

19th Annual Conference of the Robotics Society of Japan (September 18-20, 2001) Proceedings, P1279-1280

  In the object detection apparatus, in order to detect the movement of an object, first, it is necessary to specify the center position of the object whose movement is to be detected. In this case, for example, by extracting only distance information below a predetermined distance from the distance information of the object obtained by the distance detection method described above based on a threshold related to the distance, The planar shape is extracted. Then, the movement of the detection target object is detected by specifying the center position of the object from the extracted planar shape and tracking the center position of the object at a predetermined time interval.

  In this case, when the detection target object is positioned farther than the threshold value related to the distance, the two-dimensional plane shape as the motion detection target cannot be properly extracted, and the motion of the object can be detected. There is a possibility that it cannot be done.

  The present invention has been made in view of this point, and an object of the present invention is to provide an object detection apparatus that can appropriately recognize an object shape regardless of the position of a detection target object.

A main aspect of the present invention relates to an object detection apparatus that detects an object from a target area. The object detection apparatus according to this aspect includes an information acquisition unit that acquires three-dimensional distance information related to a distance to each reference position set in a target region, and the reference positions obtained from the three-dimensional distance information. An object detection unit that generates binarization information obtained by binarizing the distance at each reference position by comparing the distance and a predetermined threshold, and detects the shape of the object from the binarization information; Prepare. The object detection unit changes the threshold according to a change in distance to an object to be detected.

  ADVANTAGE OF THE INVENTION According to this invention, the object detection apparatus which can recognize an object shape appropriately irrespective of the position of a detection target object can be provided.

  The effects and significance of the present invention will become more apparent from the following description of embodiments. However, the embodiment described below is merely an example when the present invention is implemented, and the present invention is not limited to the following embodiment.

It is a figure which shows the structure of the object detection apparatus which concerns on embodiment. It is a figure which shows the structure of the object detection apparatus and information processing apparatus which concern on embodiment. It is a figure which shows the irradiation state of the laser beam with respect to the target area | region which concerns on embodiment, and the light reception state of the laser beam on an image sensor. It is a figure explaining the production | generation method of the reference pattern which concerns on embodiment. It is a figure explaining the distance detection method which concerns on embodiment. It is a figure explaining the object detection method which concerns on embodiment. It is a figure explaining the shape extraction method of the object concerning an embodiment. It is a flowchart concerning the object detection which concerns on embodiment. It is a flowchart concerning the object detection which concerns on embodiment. It is a figure which shows the example of the threshold value setting concerning the object detection which concerns on embodiment. It is a figure which shows the structure of the object detection apparatus and information processing apparatus which concern on the example of a change. It is a flowchart concerning the object detection which concerns on the example of a change. It is a figure which shows the example of the threshold value setting concerning the object detection which concerns on the example of a change. It is a figure which shows the example concerning the flowchart concerning the object detection which concerns on the example of a change, and the threshold value setting concerning an object detection.

  Embodiments of the present invention will be described below with reference to the drawings. In this embodiment, an information acquisition device of a type that acquires a three-dimensional distance information by irradiating a target region with a laser beam having a predetermined dot pattern, and two-dimensional distance information acquired by the information acquisition device, 2 A type of object detection device that generates a digitized image and detects the shape and motion of the object is illustrated.

  First, FIG. 1 shows a schematic configuration of an object detection apparatus 1 according to the present embodiment. As shown in the figure, the object detection device 1 includes an information acquisition device 2 and an information processing device 3. The television 4 is controlled by a signal from the information processing device 3.

  The information acquisition device 2 projects infrared light over the entire target area, and receives the reflected light with a CMOS image sensor, whereby the distance between each part of the object in the target area (hereinafter referred to as “three-dimensional distance information”). To get. The acquired three-dimensional distance information is sent to the information processing apparatus 3 via the cable 5.

  The information processing device 3 is, for example, a television control controller, a game machine, a personal computer, or the like. The information processing device 3 detects an object in the target area based on the three-dimensional distance information received from the information acquisition device 2, and controls the television 4 based on the detection result.

For example, the information processing device 3 detects a person based on the received three-dimensional distance information and detects the movement of the person from the change in the three-dimensional distance information. For example, when the information processing device 3 is a television control controller, the information processing device 3 detects the person's gesture from the received three-dimensional distance information and outputs a control signal to the television 4 in accordance with the gesture. The application program to be installed is installed. In this case, the user can cause the TV 4 to execute predetermined functions such as channel switching and volume up / down by making a predetermined gesture while watching the TV 4.

  For example, when the information processing device 3 is a game machine, the information processing device 3 detects the person's movement from the received three-dimensional distance information, and displays a character on the television screen according to the detected movement. An application program that operates and changes the game battle situation is installed. In this case, the user can experience a realistic sensation of playing the game as a character on the television screen by making a predetermined movement while watching the television 4.

  FIG. 2 is a diagram illustrating the configuration of the information acquisition device 2 and the information processing device 3.

  The information acquisition apparatus 2 includes a projection optical system 100 and a light receiving optical system 200 as a configuration of the optical unit. The projection optical system 100 and the light receiving optical system 200 are arranged in the information acquisition device 2 so as to be aligned in the X-axis direction.

  The projection optical system 100 includes a laser light source 110, a collimator lens 120, a mirror 130, and a diffractive optical element (DOE) 140. The light receiving optical system 200 includes an aperture 210, an imaging lens 220, a filter 230, and a CMOS image sensor 240. In addition, the information acquisition apparatus 2 includes a CPU (Central Processing Unit) 21, a laser driving circuit 22, an imaging signal processing circuit 23, an input / output circuit 24, and a memory 25 as a circuit unit.

  The laser light source 110 outputs laser light in a narrow wavelength band having a wavelength of about 830 nm in a direction away from the light receiving optical system 200 (X-axis negative direction). The collimator lens 120 converts the laser light emitted from the laser light source 110 into light slightly spread from parallel light (hereinafter simply referred to as “parallel light”).

  The mirror 130 reflects the laser light incident from the collimator lens 120 side in the direction toward the DOE 140 (Z-axis direction).

  The DOE 140 has a diffraction pattern on the incident surface. Due to the diffractive action of this diffraction pattern, the laser light incident on the DOE 140 is converted into laser light having a predetermined dot pattern and irradiated onto the target area.

  The diffraction pattern of the DOE 140 has, for example, a structure in which a step type diffraction hologram is formed in a predetermined pattern. The diffraction hologram is adjusted in pattern and pitch so as to convert the laser light converted into parallel light by the collimator lens 120 into laser light of a dot pattern.

  The DOE 140 irradiates the target region with the laser beam incident from the mirror 130 as a laser beam having a dot pattern that spreads radially. The size of each dot in the dot pattern depends on the beam size of the laser light when entering the DOE 140.

  The laser light reflected from the target area enters the imaging lens 220 via the aperture 210.

  The aperture 210 stops the light from the outside so as to match the F number of the imaging lens 220. The imaging lens 220 collects the light incident through the aperture 210 on the CMOS image sensor 240. The filter 230 is an IR filter (Infrared Filter) that transmits light in the infrared wavelength band including the emission wavelength (about 830 nm) of the laser light source 110 and cuts the wavelength band of visible light.

  The CMOS image sensor 240 receives the light collected by the imaging lens 220 and outputs a signal (charge) corresponding to the amount of received light to the imaging signal processing circuit 23 for each pixel. Here, in the CMOS image sensor 240, the output speed of the signal is increased so that the signal (charge) of the pixel can be output to the imaging signal processing circuit 23 with high response from the light reception in each pixel.

  The CPU 21 controls each unit according to a control program stored in the memory 25. With this control program, the CPU 21 is provided with the functions of a laser control unit 21a for controlling the laser light source 110 and a distance acquisition unit 21b for generating three-dimensional distance information.

  The laser drive circuit 22 drives the laser light source 110 according to a control signal from the CPU 21.

  The imaging signal processing circuit 23 controls the CMOS image sensor 240 and sequentially takes in the signal (charge) of each pixel generated by the CMOS image sensor 240 for each line. Then, the captured signals are sequentially output to the CPU 21. Based on the signal (imaging signal) supplied from the imaging signal processing circuit 23, the CPU 21 calculates the distance from the information acquisition device 2 to each part of the detection target by processing by the distance acquisition unit 21b. The input / output circuit 24 controls data communication with the information processing device 3.

  The information processing apparatus 3 includes a CPU 31, an input / output circuit 32, and a memory 33. In addition to the configuration shown in the figure, the information processing apparatus 3 is configured to communicate with the television 4 and to read information stored in an external memory such as a CD-ROM and install it in the memory 33. However, the configuration of these peripheral circuits is not shown for the sake of convenience.

  The CPU 31 controls each unit according to a control program (application program) stored in the memory 33. With this control program, the CPU 31 is provided with the functions of an object detection unit 31a for detecting an object in the image and a function control unit 31b for controlling the function of the television 4 according to the movement of the object. . Such a control program is read from a CD-ROM by a drive device (not shown) and installed in the memory 33, for example.

  The object detection unit 31a extracts the shape of the object in the image from the three-dimensional distance information supplied from the information acquisition device 2, and detects the movement of the extracted object shape. Here, the object detection unit 31a generates a binarized image in order to extract only the planar shape of the object from the three-dimensional distance information supplied from the information acquisition device 2 based on the threshold regarding the distance. Thereafter, the generated binarized image is compared with the object shape extraction template for extracting the object shape stored in the memory 33, and the object shape to be extracted from the motion and the object shape in the three-dimensional distance information are compared. Specify the center position of. In this way, the object detection unit 31a detects the movement of the object by tracking the distance information of the center position of the specified object shape every predetermined time.

For example, when the control program is a game program, the function control unit 31b performs a process for causing the character on the television screen to operate according to the movement (gesture) of the person detected by the object detection unit 31a. Is done.

  When the control program stored in the memory 33 is a program for controlling the function of the television 4, the function control unit 31 b uses the signal of the television 4 from the object detection unit 31 a based on a human motion (gesture). Processing for controlling functions (channel switching, volume adjustment, etc.) is executed.

  The input / output circuit 32 controls data communication with the information acquisition device 2.

  The projection optical system 100 and the light receiving optical system 200 are installed side by side with a predetermined distance in the X axis direction so that the projection center of the projection optical system 100 and the imaging center of the light receiving optical system 200 are aligned on a straight line parallel to the X axis. Is done.

  The installation interval between the projection optical system 100 and the light receiving optical system 200 is set according to the distance between the information acquisition device 2 and the reference plane of the target area. The distance between the reference plane and the information acquisition device 2 varies depending on how far away the target is to be detected. The closer the distance to the target to be detected is, the narrower the installation interval between the projection optical system 100 and the light receiving optical system 200 is. Conversely, as the distance to the target to be detected increases, the installation interval between the projection optical system 100 and the light receiving optical system 200 increases.

  First, a method for acquiring three-dimensional distance information by the information acquisition device 2 will be described.

  FIG. 3A is a diagram schematically showing the irradiation state of the laser light on the target region, and FIG. 3B is a diagram schematically showing the light receiving state of the laser light in the CMOS image sensor 240. For convenience, FIG. 3B shows a flat surface (screen) in the target area and a light receiving state when a person is present in front of the screen.

  As shown in FIG. 3A, the projection optical system 100 irradiates a target region with laser light having a dot pattern (hereinafter, the entire laser light having this pattern is referred to as “DP light”). . In FIG. 3A, the light flux region of DP light is indicated by a solid line frame. In the light flux of DP light, dot regions (hereinafter simply referred to as “dots”) generated by the diffraction action by the DOE 140 are scattered according to the dot pattern by the diffraction action by the DOE 140.

  When a flat surface (screen) exists in the target area, DP light reflected thereby is distributed on the CMOS image sensor 240 as shown in FIG.

  In FIG. 3B, the entire DP light receiving area on the CMOS image sensor 240 is indicated by a broken line frame, and the DP light receiving area incident on the imaging effective area of the CMOS image sensor 240 is indicated by a solid line frame. Has been. The effective imaging area of the CMOS image sensor 240 is an area where the CMOS image sensor 240 receives a DP light and outputs a signal as a sensor, and has a size of, for example, VGA (horizontal 640 pixels × vertical 480 pixels). . Further, the light of Dt0 on the target area shown in FIG. 10A enters the position of Dt′0 shown in FIG. An image of a person in front of the screen is taken upside down on the CMOS image sensor 240 in the vertical and horizontal directions.

  Here, the distance detection method will be described with reference to FIGS.

  FIG. 4 is a diagram for explaining a reference pattern setting method used in the distance detection method.

  As shown in FIG. 4A, a flat reflection plane RS perpendicular to the Z-axis direction is disposed at a position at a predetermined distance Ls from the projection optical system 100. The emitted DP light is reflected by the reflection plane RS and enters the CMOS image sensor 240 of the light receiving optical system 200. Thereby, an electrical signal for each pixel in the effective imaging area is output from the CMOS image sensor 240. The output electric signal value (pixel value) for each pixel is developed on the memory 25 of FIG.

  Hereinafter, an image including all pixel values obtained by reflection from the reflection surface RS is referred to as a “reference image”, and the reflection surface RS is referred to as a “reference surface”. Then, as shown in FIG. 4B, a “reference pattern region” is set on the standard image. FIG. 4B shows a state in which the light receiving surface is seen through in the positive direction of the Z axis from the back side of the CMOS image sensor 240. The same applies to the drawings after FIG.

  A plurality of segment areas having a predetermined size are set for the reference pattern area set in this way. The size of the segment area is determined in consideration of the contour extraction accuracy of the object based on the obtained distance information, the load of the calculation amount of distance detection for the CPU 21, and the error occurrence rate by the distance detection method described later. In the present embodiment, the size of the segment area is set to 15 horizontal pixels × 15 vertical pixels.

  With reference to FIG.4 (c), the segment area | region set to a reference pattern area | region is demonstrated. In FIG. 4C, for the sake of convenience, the size of each segment area is indicated by 9 pixels wide × 9 pixels high, and the center pixel of each segment area is indicated by a cross.

  As shown in FIG. 4C, the segment areas are set such that adjacent segment areas are arranged at intervals of one pixel in the X-axis direction and the Y-axis direction with respect to the reference pattern area. That is, a certain segment area is set at a position shifted by one pixel with respect to a segment area adjacent to the segment area in the X-axis direction and the Y-axis direction. At this time, each segment area is dotted with dots in a unique pattern. Therefore, the pattern of pixel values in the segment area is different for each segment area. The narrower the interval between adjacent segment areas, the greater the number of segment areas included in the reference pattern area, and the resolution of distance detection in the in-plane direction (XY plane direction) of the target area is enhanced.

  Thus, information on the position of the reference pattern area on the CMOS image sensor 240, pixel values (reference patterns) of all pixels included in the reference pattern area, and segment area information set for the reference pattern area are shown in FIG. 2 memory 25. These pieces of information stored in the memory 25 are hereinafter referred to as “reference templates”.

  The CPU 21 in FIG. 2 refers to the reference template when calculating the distance from the projection optical system 100 to each part of the detection target object. When calculating the distance, the CPU 21 calculates the distance to each part of the object based on the shift amount of the dot pattern in each segment area obtained from the reference template.

  For example, as shown in FIG. 4A, when an object is present at a position closer than the distance Ls, DP light (DPn) corresponding to a predetermined segment area Sn on the reference pattern is reflected by the object, and the segment area Sn. It is incident on a different region Sn ′. Since the projection optical system 100 and the light receiving optical system 200 are adjacent to each other in the X-axis direction, the displacement direction of the region Sn ′ with respect to the segment region Sn is parallel to the X-axis. In the case of FIG. 4A, since the object is located at a position closer than the distance Ls, the region Sn 'is displaced in the X-axis positive direction with respect to the segment region Sn. If the object is at a position farther than the distance Ls, the region Sn ′ is displaced in the negative X-axis direction with respect to the segment region Sn.

  Based on the displacement direction and displacement amount of the region Sn ′ with respect to the segment region Sn, the distance Lr from the projection optical system 100 to the part of the object irradiated with DP light (DPn) is triangulated using the distance Ls. Calculated based on Similarly, the distance from the projection optical system 100 is calculated for the part of the object corresponding to another segment area. The details of this calculation method are described in, for example, Non-Patent Document 1 (The 19th Annual Conference of the Robotics Society of Japan (September 18-20, 2001) Proceedings, P1279-1280).

  In this distance calculation, it is detected to which position the segment area Sn of the reference template has been displaced during actual measurement. This detection is performed by collating the dot pattern obtained from the DP light irradiated onto the CMOS image sensor 240 at the time of actual measurement with the dot pattern included in the segment region Sn. Hereinafter, an image made up of all the pixel values obtained from the DP light irradiated to the imaging effective area on the CMOS image sensor 240 at the time of actual measurement will be referred to as “measured image”. The effective imaging area of the CMOS image sensor 240 at the time of actual measurement is, for example, the size of VGA (horizontal 640 pixels × vertical 480 pixels), as in the case of acquiring the reference image.

  FIGS. 5A to 5E are diagrams for explaining such a distance detection method. FIG. 5A is a diagram showing a reference pattern area set in a standard image on the CMOS image sensor 240, and FIG. 5B is a diagram showing an actually measured image on the CMOS image sensor 240 at the time of actual measurement. FIG. 5C to FIG. 5E are diagrams for explaining a collation method between the DP light dot pattern included in the actual measurement image and the dot pattern included in the segment area of the reference template. For convenience, FIGS. 5 (a) and 5 (b) show only a part of the segment areas, and FIGS. 5 (c) to 5 (e) show the size of each segment area. It is shown by pixel × 9 pixels vertically. 5B, for the sake of convenience, as shown in FIG. 4B, there is a person in front of the reference plane as a detection target object, and an image of the person is reflected. It is shown.

  When searching for the displacement position at the time of actual measurement of the segment area Si in FIG. 5A, as shown in FIG. 5B, the search area Ri is set for the segment area Si on the actual measurement image. The search area Ri has a predetermined width in the X-axis direction. The segment area Si is sent one pixel at a time in the search area Ri in the X-axis direction, and the dot pattern of the segment area Si is compared with the dot pattern on the measured image at each feed position. Hereinafter, a region corresponding to each feed position on the actually measured image is referred to as a “comparison region”. A plurality of comparison areas having the same size as the segment area Si are set in the search area Ri, and the comparison areas adjacent in the X-axis direction are shifted by one pixel from each other.

  The width of the search area Ri is determined by the direction in which the detection target object is away from the information acquisition device 2 with respect to the reference plane and how much distance is in the detectable direction. In FIG. 5, a shift of x pixels in the X-axis positive direction from a position shifted by x pixels in the negative X-axis direction from the pixel position (center pixel position) on the measured image corresponding to the pixel position of the segment region Si on the reference image. The search area Ri is set so that the segment area Si is sent in the specified range (hereinafter referred to as “search range L0”).

  In the present embodiment, the range from the position shifted by −30 pixels from the center pixel position to the position shifted by +30 pixels is set as the search range L0.

At the time of distance detection, the segment area Si is fed one pixel at a time in the X-axis direction in the search area Ri, and at each feed position, the dot pattern of the segment area Si stored in the reference template and the dot pattern of the DP light of the measured image The degree of matching is required. As described above, the segment area Si is sent only in the X-axis direction in the search area Ri as described above. Normally, the dot pattern of the segment area set by the reference template is a predetermined value in the X-axis direction at the time of actual measurement. This is because the displacement occurs only within the range.

  At the time of actual measurement, depending on the position of the detection target object, the dot pattern corresponding to the segment area may protrude from the actual measurement image in the X-axis direction. For example, when a dot pattern corresponding to the segment area S1 on the negative X-axis side of the reference pattern area is reflected by an object at a distance farther than the reference plane, the dot pattern corresponding to the segment area S1 is X more than the measured image. Positioned in the negative axis direction. In this case, since the dot pattern corresponding to the segment area is not within the effective imaging area of the CMOS image sensor 240, the segment area cannot be properly matched. However, since it is possible to perform matching appropriately in areas other than the end segment areas, there is little influence on object distance detection.

  In addition, when matching is performed appropriately for the end region, the effective imaging region of the CMOS image sensor 240 at the time of actual measurement may be made larger than the effective imaging region of the CMOS image sensor 240 at the time of acquiring the reference image. What can be used should be used. For example, when an effective imaging area is set with a size of VGA (horizontal 640 pixels × vertical 480 pixels) at the time of acquiring a reference image, 30 pixels in the X-axis positive direction and X-axis negative direction than that when actually measured. The effective imaging area is set by a size that is larger. As a result, the actually measured image becomes larger than the reference image, but matching can be appropriately performed for the end segment area.

  When the matching degree is detected, first, the pixel value of each pixel in the reference pattern area and the pixel value of each pixel in each segment area of the actually measured image are binarized and stored in the memory 25. For example, when the pixel values of the reference image and the actually measured image are 8-bit gradations, among the pixel values of 0 to 255, the pixels that are equal to or greater than the predetermined threshold are the pixel values 1 and the pixels that are less than the predetermined threshold are pixels The value is converted to 0 and held in the memory 25. Thereafter, the similarity between the comparison region and the segment region Si is obtained. That is, the difference between the pixel value of each pixel in the segment area Si and the pixel value of the corresponding pixel in the comparison area is obtained. A value Rsad obtained by adding the obtained difference to all the pixels in the comparison region is acquired as a value indicating the similarity.

  For example, as shown in FIG. 5C, when pixels in n columns × m rows are included in one segment area, the pixel values T (i, j) of the pixels in i columns and j rows in the segment area. ) And the pixel value I (i, j) of the pixel in the comparison area i column and j row. Then, the difference is obtained for all the pixels in the segment area, and the value Rsad of the equation shown in FIG. 5C is obtained from the sum of the differences. The smaller the value Rsad, the higher the degree of similarity between the segment area and the comparison area.

  Thus, as shown in FIG. 5D, the value Rsad is obtained for all the comparison regions of the search region Ri for the segment region Si. FIG. 5E is a graph schematically showing the value Rsad at each feed position in the search area Ri. When the value Rsad is obtained for all the comparison regions of the search region Ri for the segment region Si, first, the minimum value Bt1 is referred to from the obtained value Rsad. Next, the second smallest value Bt2 is referred to from the obtained value Rsad. If the position of the minimum value Bt1 and the second smallest value Bt2 are two pixels or more away from each other and the difference value Es is less than the threshold value, the search for the segment area Si is regarded as an error. On the other hand, if the difference value Es is equal to or greater than the threshold value, the comparison area Ci corresponding to the minimum value Bt1 is determined as the movement area of the segment area Si.

For example, as shown in FIG. 5D, the comparison area Ci corresponding to the segment area Si is in the positive direction of the X axis with respect to the pixel position Si0 on the measured image at the same position as the pixel position of the segment area Si on the reference image. It is detected at a position shifted by α pixels. This is because the dot pattern of the DP light on the measured image is displaced in the X-axis positive direction from the segment area Si0 on the reference image by a detection target object (person) that is present at a position closer to the reference plane. Note that as the size of the segment region Si increases, the uniqueness of the dot pattern included in the segment region Si increases and the error rate decreases. For example, when the size of the segment region Si is set to 15 pixels wide × 15 pixels vertically, the distance detection usually does not cause an error, and matching can be performed appropriately.

  Thus, when the displacement position of each segment region is searched from the dot pattern of DP light acquired at the time of actual measurement, detection corresponding to each segment region is performed by triangulation based on the displacement position as described above. The distance to the part of the target object is obtained.

  In this manner, the same segment area search is performed for all the segment areas from the segment area S1 to the segment area Sn.

  The information acquisition device 2 stores the distance to the detection target object corresponding to each segment area acquired as described above in the memory 25 as an image assigned to pixel values expressed in white to black gradations. . Hereinafter, an image in which a distance corresponding to each segment area is expressed by a pixel value is referred to as a “distance image”. As described above, in the present embodiment, since the segment area is set in increments of one pixel with respect to the reference pattern area of the standard image, the distance image has a resolution (substantially approximately the same VGA size as the standard image). 640 × approximately 480). The gradation of the pixel of the distance image is an 8-bit gradation, and a gradation closer to white (pixel value 255) is assigned to the closer distance, and a gradation closer to black (pixel value 0) is assigned to the longer distance. If the segment area search results in an error, a gray scale of black (pixel value 0) is assigned. The information acquisition device 2 outputs the distance image to the information processing device 3 as the three-dimensional distance information of the detection target object at predetermined time intervals. In the present embodiment, the information acquisition device 2 generates 30 distance images per second and outputs them to the information processing device 3. Hereinafter, one distance image is referred to as one frame.

  Next, a method for extracting the shape of the object from the distance image and a method for detecting the movement of the object in the object detection unit 31a of the information processing device 3 will be described.

  FIG. 6A is a diagram illustrating an example of a distance image obtained by acquiring the distance of a person as a detection target object. FIG. 6B is a diagram illustrating an example of an image obtained by binarizing the distance image with a predetermined threshold. FIG. 6C is a diagram for explaining an object shape extraction from a binarized image and a center-of-gravity extraction method. FIG. 6D is a diagram for explaining a method for detecting the movement of an object. Here, a method for extracting the movement of the right hand of a person will be described as an example.

  With reference to Fig.6 (a), as mentioned above, the information acquisition apparatus 2 performs three-dimensional distance measurement, and the distance image Pi is produced | generated for every predetermined time. The distance image Pi shows an image when the distance is acquired with the person protruding his / her hand forward, and the position of the hand is the whitest and the rest of the person has a gradation close to black. It is shown. In addition, in the background other than the person, no object is detected, and the background is substantially black.

  In order to detect the movement of the right hand of the person from the distance image Pi output from the information acquisition device 2, the object detection unit 31a specifies the center-of-gravity position Gi (pixel position of the distance image) that is the center position of the movement. . In order to detect the center of gravity position Gi of the right hand, the object detection unit 31a first generates a binarized image Mi in which the distance image Pi is expressed only in white and black as shown in FIG. The shape of the contour Eg of the right hand is extracted.

As described above, the gradation of the pixel of the distance image Pi corresponds to the distance of the object in the direction away from the information acquisition device 2 (Z-axis direction). By setting the binarization threshold Dsh for generating the binarized image Mi to a value corresponding to a distance a little farther than the distance of the object whose shape is to be extracted from the distance image Pi, Only the shape of the object can be extracted.

  For example, when extracting the right hand of a person, in the distance image Pi of FIG. 6A, the pixel value is slightly larger than a gray pixel value corresponding to a person's torso, shoulders, etc., which is slightly close to black, and corresponds to a part of the person's hand. As a result, a value slightly smaller than the gray pixel value close to white is set as the binarization threshold value Dsh. As a result, as shown in FIG. 6B, a binary image Mi in which only the hand portion of the person is expressed in white is generated.

  Next, the object shape extraction template stored in the memory 33 shown in FIG. 2 is referred to in advance by the contour extraction engine that extracts the contour of the predetermined object, and the object to be detected from the binarized image Mi. A contour of the shape is detected. It should be noted that the object shape extraction template includes pixel information indicating the shape of the object to be detected for motion. The object contour extraction engine extracts the contour of the shape of the object to be matched by comparing the pixel information of the object shape extraction template with the pixel information of the binarized image Mi by a predetermined detection method. Here, an object shape extraction template for extracting the contour Eg of the human right hand is referred to.

  Thus, after detecting the right hand contour Eg in the binarized image Mi, the center-of-gravity position Gi is calculated from the contour Eg. Thereby, it is detected in which position (pixel position) the shape to be detected for motion is located in the distance image Pi.

  Then, as shown in FIG. 6C, when the right hand centroid position Gi is detected in the binarized image Mi, the pixel position and the pixel value of the right hand centroid position Gi in the distance image Pi are referred to. Three-dimensional distance information Ti (tx, ty, tz) of the center of gravity of the right hand is calculated. Note that the centroid position Gi of the distance image Pi and the centroid position Gi of the binarized image Mi are the same position. That is, the pixel position in the X-axis direction of the centroid position Gi in the distance image Pi corresponds to tx of the three-dimensional distance information Ti, and the pixel position in the Y-axis direction of the centroid position Gi in the distance image Pi is ty of the three-dimensional distance information Ti. The pixel value of the gravity center position Gi in the distance image Pi corresponds to tz of the three-dimensional distance information Ti. Thereby, the three-dimensional distance information Ti of the right hand at the timing when the distance image Pi is generated is acquired.

  Similarly, the right-hand three-dimensional distance information Ti + 1 to 1 is acquired for the distance images Pi + 1 and subsequent acquired at each distance acquisition timing. Then, by monitoring the change in the three-dimensional distance information between the distance acquisition timings, it is possible to detect the movement of the right hand in the three-dimensional space as shown in FIG. For example, in FIG. 6D, the three-dimensional distance information Ti (tx, ty, tz) changes from the three-dimensional distance information Ti + 1 (tx + α, ty + β, tz + γ) between predetermined distance acquisition timings. It can be detected that the position of has changed by α in the X-axis direction, β in the Y-axis direction, and γ in the Z-axis direction.

  FIG. 7A is a schematic view of the projection optical system 100 and the light receiving optical system 200 viewed from the Y-axis direction. 7B to 7D are diagrams illustrating examples of the binarized image Mi corresponding to the distance of the person H. FIG.

  6A to 6D, as shown in FIG. 7A, the person H is located at a distance Zb from the light receiving optical system 200, and the binarization threshold Dsh is larger than the shoulder Hs of the person H. The example of the object detection in the case of being located ahead and behind the hand Ha of the person H is shown. In such a case, as shown in FIG. 7B, only the shape of the hand Ha of the person H that is closer to the binarization threshold Dsh is extracted.

However, for example, the distance image Pi is acquired when the person H is located at a distance Zc far from the distance Zb and all the parts of the person H are far away from the position corresponding to the binarization threshold Dsh. When binarization is performed using the binarization threshold Dsh, the shape of the person's hand H and the shape of the person H cannot be extracted as shown in FIG. Therefore, when the motion detection target object is positioned farther than the position corresponding to the binarization threshold value Dsh, the movement of the object cannot be properly followed.

  Further, for example, when the person H is located at a position closer to the distance Za than the distance Zb, and all the parts of the person H are closer to the position corresponding to the binarization threshold Dsh, the distance image Pi is displayed. When obtained and binarized with the binarization threshold value Dsh, as shown in FIG. 7D, not only the shape of the person's hand H but also all the shapes such as the torso and shoulders of the person H are binarized images Mi. Will be included. In this case, it is difficult to extract the shape of the contour Eg of the right hand as compared with the case of FIG. For example, in FIG. 7D, the boundary portion between the hand and the torso portion is the same white pixel information. Therefore, the hand cannot be properly extracted unless the contour is extracted more accurately.

  Thus, when the binarization threshold value Dsh is a fixed value, there is a possibility that the shape and movement of the object cannot be detected properly if the object to be extracted is moved in the front-rear direction.

  Therefore, in the present embodiment, the binarization threshold is appropriately set according to the change in the distance in the front-rear direction of the object so that the shape and movement of the object can be properly detected even if the detection target object moves back and forth. Set Dsh. If the shape of the object cannot be recognized, an appropriate value of the binarization threshold Dsh is searched and the binarization threshold Dsh is set to an appropriate value.

  8 and 9 are flowcharts showing processing for detecting an object while changing the binarization threshold Dsh. 8 and 9 are performed by the function of the object detection unit 31 a of the CPU 31 of the information processing device 3.

  In addition, the control process concerning the search of the binarization threshold value described in FIGS. 8 and 9 is an example of the process described in claims 2 and 3. Moreover, the process concerning S207 of FIG. 9 is an example of the process of Claim 5.

  First, the CPU 31 sets 1 to a variable i indicating the number of frames of the distance image and 0 to a variable k for checking whether the object detection operation is started (S101). Then, the CPU 31 determines whether or not it is time to generate a distance image and extract a shape (S102). When it is not the shape extraction timing (S102: NO), the CPU 31 waits for the process until the shutdown (S103: NO).

  When the shape extraction timing comes (S102: YES), the CPU 31 determines whether or not the variable k is 0 (S104). Thereby, it is determined whether or not the distance image Pi to be processed is the first frame at the start of the object detection operation. When the distance image Pi to be processed is the first frame at the start of the object detection operation (S104: YES), the CPU 31 sets 1 to the variable k (S105). After that, the CPU 31 advances the processing to S201 in FIG. 9 and first searches for an appropriate binarization threshold Dsh and initializes the binarization threshold Dsh.

  When searching for the binarization threshold value Dsh, the CPU 31 first sets the binarization threshold value Dsh to an initial value D0 corresponding to the closest possible position (S201). Then, the CPU 31 binarizes the distance image Pi with the set binarization threshold Dsh to generate a binarized image Mi (S202). As a result, only the shape of the object located at a shorter distance than the distance corresponding to the initial value D0 is extracted. Thereafter, the CPU 31 detects the hand outline Eg from the binarized image Mi (S203), and determines whether the hand outline Eg has been detected (S204).

  When the hand outline Eg cannot be detected (S204: NO), the CPU 31 subtracts ΔD corresponding to a predetermined distance from the binarization threshold Dsh (S205). Then, the CPU 31 determines whether or not the binarization threshold value Dsh is lower than a threshold value Dsm corresponding to a predetermined long distance position (S206). When the binarization threshold value Dsh is not lower than the threshold value Dsm (S206: NO), the CPU 31 returns the process to S202, whether the hand outline Eg is detected (S204: YES), or the binarization threshold value Dsh is Until the threshold value Dsm is lowered (S206: YES), the extraction of the hand outline Eg is repeated while gradually shifting the binarization threshold value Dsh to a far distance position.

  An example of the setting state of the binarization threshold value Dsh will be described with reference to FIGS.

  Referring to FIG. 10A, for example, when the person H is located at the position of the distance Zc, the binarization threshold Dsh is first set to the initial value D0 corresponding to the position of the short distance. In this case, since the person H is not positioned ahead of the binarization threshold Dsh, the shape of the person H cannot be extracted. Therefore, in this case, NO is determined in S204 of FIG. 9, and the binarization threshold Dsh is decreased by ΔD. As a result, the position corresponding to the binarization threshold value Dsh is shifted to a distant position by a distance corresponding to ΔD. Thereafter, the position corresponding to the binarization threshold Dsh is gradually shifted to a distant position by a distance corresponding to ΔD until the hand outline Eg is extracted. Then, as shown in FIG. 10B, when the binarization threshold value Dsh becomes a value corresponding to a position far from the hand Ha of the person H, YES is determined in S204 of FIG. If the hand Ha of the person H is not positioned between D0 and Dsm and the hand outline Eg is not extracted, YES is determined in S206 of FIG.

  Returning to FIG. 9, if YES is determined in S <b> 206, the CPU 31 returns the process to S <b> 101 in FIG. 8, assuming that the shape of the detection target object cannot be detected within a predetermined distance. If YES is determined in S204, the CPU 31 subtracts ΔDo corresponding to the predetermined distance from the binarization threshold Dsh, assuming that the shape of the detection target object can be detected within the predetermined distance (S207). Thereby, the binarization threshold value Dsh is set to a value corresponding to a position a little farther than the position where Ha of the person H is detected, as shown in FIG. Thus, the binarization threshold value Dsh is set to a value corresponding to a position slightly further away than the value corresponding to the position where the hand Ha of the person H is detected. Even if it moves in the positive direction), the distance of the hand Ha does not immediately exceed the binarization threshold value Dsh, and the movement of the hand Ha can be detected appropriately.

  In this way, a value corresponding to an appropriate position of the binarization threshold value Dsh of the first frame is searched, and the binarization threshold value Dsh is set. When the binarization threshold Dsh for the first frame is set, the CPU 31 advances the processing to S106 in FIG.

  The CPU 31 binarizes the distance image Pi with the binarization threshold Dsh set as described above to generate a binarized image Mi (S106), and detects the hand outline Eg from the binarized image Mi. (S107). Then, the CPU 31 determines whether or not the hand outline Eg has been detected (S108). When the hand outline Eg cannot be detected (S108: NO), the CPU 31 executes the processes of S201 to S207 in FIG. 9 again to search for an appropriate binarization threshold value Dsh. When the hand outline Eg can be detected (S108: YES), the CPU 31 calculates the center-of-gravity position Gi of the hand from the detected outline Eg of the binarized image Mi by a predetermined calculation process (S109). Then, the CPU 31 acquires the three-dimensional distance information Ti (tx, ty, tz) of the center of gravity Gi of the hand from the distance image Pi (S110). Thereby, the position of the hand for detecting the movement at the time of acquiring the distance image Pi is specified.

Thus, when the position of the hand is specified, the CPU 31 determines whether or not the variable i is 10 (S111). Thereby, it is determined whether the frame of the distance image Pi to be processed is the 10th frame. When the frame of the distance image Pi to be processed is not the 10th frame (S111: NO), the CPU 31 adds 1 to the variable i (S112), and returns the process to S102. As a result, for the next frame, detection of the shape of the hand to be motion-detected and acquisition of the three-dimensional distance information Ti are performed. In this case, since the process is for the second and subsequent frames, NO is determined in S104, and in S106, the binarized image Mi is generated using the binarization threshold Dsh set at that timing. If the hand outline Eg cannot be extracted from the binarized image Mi (S108: NO), the process of FIG. 9 is executed again, the binarization threshold Dsh is reset, and the process returns to S106. Processing based on the reset binarization threshold value Dsh is performed.

  The movement of the hand can be detected by following the change in the three-dimensional distance information Ti of the center-of-gravity position Gi of the hand obtained in each frame.

  When the object shape detection and the acquisition of the three-dimensional distance information Ti are completed up to the tenth frame, it is determined YES in S111, and the CPU 31 sets the binarization threshold Dsh to the three-dimensional distance information Ti of the first to tenth frames. ˜Ti-9 is set to a value Da corresponding to the distance of the Z-axis position information tz of the three-dimensional distance information Ti acquired immediately before (S211). Thereafter, the CPU 31 subtracts ΔDo corresponding to a predetermined distance from the binarization threshold Dsh (S212). Then, the CPU 31 sets 1 to the variable i (S213), returns the process to S102, and executes the object detection process for 10 frames again. As a result, as shown in FIG. 10D, even if the position of the hand Ha of the person H varies by Δh, the binarization threshold value Dsh is obtained immediately before the binarization threshold Dsh distance. Therefore, even if the position of the hand Ha of the person H fluctuates, the binarization threshold Dsh does not become a value corresponding to the position in front of the person Ha, and the detection of the shape of the object has failed. It becomes difficult to do. Similarly to S207 described above, the binarization threshold value Dsh is set to a value that corresponds to a position that is slightly further away than the value that corresponds to the position where the hand Ha of the person H is detected. Even if Ha moves far away (Z-axis positive direction), the distance of the hand Ha does not immediately exceed the binarization threshold value Dsh, and the movement of the hand Ha can be well tracked and detected. .

  As described above, according to the present embodiment, since the binarization threshold value Dsh is set according to the position of the detection target object, it is possible to properly detect the shape and movement of the object even if the distance of the object fluctuates. Can do.

  Further, according to the present embodiment, when the shape of the object can no longer be recognized, an appropriate value of the binarization threshold Dsh is reset by the search again, so that even if the position of the object fluctuates greatly, The shape and movement of the object can be detected properly.

  Further, according to the present embodiment, since the binarization threshold Dsh is set to a value corresponding to the distance in the Z-axis direction of the object detected immediately before every 10 frames, detection of the shape of the object has failed. It becomes difficult to do.

  Furthermore, according to the present embodiment, the binarization threshold value Dsh is set to a value that corresponds to a position that is a little farther than the value that corresponds to the position where the shape of the object is detected. However, even if the object moves far away (Z-axis positive direction), the binarization threshold Dsh is not exceeded immediately, and the movement of the object can be detected well.

  Although the embodiment of the present invention has been described above, the present invention is not limited to the above embodiment, and various modifications can be made to the embodiment of the present invention in addition to the above. .

  For example, in the above embodiment, the function of the object detection unit 31a is incorporated in the CPU 31 of the information processing device 3, but as shown in FIG. 11, it is incorporated in the CPU 21 of the information acquisition device 2 as the object detection unit 21c. May be. In this case, the object detection unit 21c detects the shape and movement of the object from the distance image acquired by the information acquisition unit, and outputs a signal corresponding to the movement of the object to the information processing device 3. The information processing device 3 controls various functions such as a television and a personal computer based on a signal corresponding to the movement of the object output from the object detection unit 21c. Furthermore, the information acquisition device 2 and the information processing device 3 may be integrated.

  In the above embodiment, the active stereo type information acquisition apparatus 2 that acquires the three-dimensional distance information by irradiating the dot pattern is shown, but the present invention is not limited to this. For example, the present invention may be applied to a passive stereo type information acquisition apparatus that acquires three-dimensional distance information from the parallax of two cameras. In addition, any apparatus may be used as long as it is an information acquisition apparatus that acquires three-dimensional distance information that can use the method for detecting the shape and motion of the object described in the above embodiment.

  In the above embodiment, in order to search for an appropriate value of the binarization threshold Dsh for detecting the contour Eg of a person's hand, the binarization threshold Dsh is gradually shifted to a value corresponding to a long distance. However, it is determined whether the hand outline Eg can be detected. First, after detecting the outline Eg2 of the whole image of the person that is relatively easy to detect, the person's shoulder outline Eg3 is detected, and then the person's hand is detected. The binarization threshold value Dsh may be searched for by detecting the contour Eg.

  FIG. 12 is a flowchart showing processing for searching for the binarization threshold value Dsh in this case. FIG. 12 is performed by the function of the object detection unit 31 a of the CPU 31 of the information processing device 3. The process of FIG. 12 is executed instead of the process of FIG. The process related to the search for the binarization threshold value Dsh is substantially the same as the process of FIG. 9, and only the changes will be described in detail.

  Note that the control processing related to the binarization threshold value search illustrated in FIG. 12 is an example of the processing according to claim 4. Moreover, the process concerning S315 of FIG. 12 is an example of the process of Claim 5.

  In this case, first, in S301 to S306, the CPU 31 searches for a binarization threshold Dsh that can detect the outline Eg2 of the entire person that is relatively easy to detect. As a result, as in the above embodiment, as shown in FIG. 13A, the binarized threshold value Dsh is searched so as to gradually move away from the short distance to the threshold value Dsm2. At this time, the person H is larger than the hand Ha, and the contour extraction is easy. Therefore, in this case, the search for the binarization threshold value Dsh can detect an appropriate value even if the accuracy is lowered to some extent. As a method of reducing the search accuracy, for example, comparison of pixel information between the binarized image Mi and the object shape template is performed every several pixels. As a result, the amount of computation required for searching for the binarization threshold value Dsh can be kept low.

Returning to FIG. 12, when the binarization threshold Dsh that can detect the contour Eg2 of the person is searched in this way (S304: YES), the CPU 31 then detects the contour Eg3 of the shoulder (S307). ). Then, the CPU 31 determines whether or not the shoulder contour Eg3 has been detected (S308). When the contour Eg2 of the person can be detected (S304: YES) but the shoulder contour Eg3 cannot be detected (S308: NO), the CPU 31 advances the process to S305 and subtracts ΔD from the binarization threshold Dsh. (S305). Then, in S302 to S308, the CPU 31 adjusts the binarization threshold value Dsh so that the contour Eg2 of the person and the contour Eg3 of the shoulder are detected. That is, the CPU 31 generates a binarized image Mi with the binarization threshold Dsh (S302), and determines whether the person's contour Eg2 and shoulder contour Eg3 can be detected based on the generated binarized image Mi. If it is determined (S304, S308) and the person's outline Eg2 or shoulder outline Eg3 cannot be detected (S304: NO or S308: NO), the person's outline Eg2 and shoulder outline Eg3 are detected ( (S304: YES and S308: YES) The binarization threshold Dsh is decreased by ΔD.

  When the contour Eg2 of the person and the contour Eg3 of the shoulder are detected in this way (S304: YES and S308: YES), the CPU 31 determines the distance ΔDn of the hand assumed from the position of the shoulder to the binarization threshold Dsh (for example, , Several tens of centimeters) is added (S309). And CPU31 adjusts the binarization threshold value Dsh so that the outline Eg of a hand can be detected in S310-S314. That is, the CPU 31 generates a binarized image Mi with the binarization threshold Dsh set in S309 (S310), and determines whether the hand outline Eg can be detected based on the generated binarized image Mi. (S311, 312) If the hand outline Eg cannot be detected (S312: YES), the binarization threshold value Dsh is decreased by ΔD until the hand outline Eg is detected (S313). Thus, when the hand outline Eg is detected (S312: YES), the CPU 31 subtracts ΔDo from the binarization threshold Dsh, as in the above embodiment (S315). The binarization threshold value after the subtraction is used for the binarization process in S106 of FIG.

  By the processing after S309, as shown in FIG. 13B, the binarization threshold value Dsh is searched so as to gradually move away from the position in front of the person H from the shoulder Hs to the threshold value Dsm3. As described above, since the search for the binarization threshold Dsh for extracting the hand contour Eg that requires a certain degree of accuracy can be suppressed to a narrow range, the amount of calculation can be reduced compared to the above embodiment. it can.

  In the above embodiment, the binarization threshold Dsh is reset every 10 frames so as to follow the position corresponding to the Z-axis distance acquired immediately before. The resetting may be performed every frame, or may be performed every other number of frames. Also, the binarization threshold value Dsh may be set to a value corresponding to the farthest position in 10 frames instead of a value corresponding to the Z-axis distance acquired immediately before. In this way, since the binarization threshold Dsh is set to a value corresponding to a position farther than the farthest distance moved most recently, the binarization threshold Dsh is a value corresponding to a position ahead of the person. Therefore, the shape of the object can be detected properly. Furthermore, in addition to the above, the binarization threshold Dsh may be set to a value corresponding to the average position of the distance in the Z-axis direction of the object.

  In the above embodiment, if the hand outline Eg cannot be detected at a distance corresponding to D0 to Dsm, the process returns to S101 in FIG. 8 and the detection of the same hand-shaped outline Eg is repeated again. However, if the hand contour Eg cannot be detected, the contour detection of the other hand shape may be performed. In this case, an object shape extraction template for both hand shapes is prepared in advance in the memory 33 of the information processing device 3, and it is possible to cope with various hand shape changes by switching between the templates and detecting them as needed.

  In the above embodiment, when the hand outline Eg cannot be detected, the binarization threshold value Dsh is always searched for within the distance corresponding to D0 to Dsm. You may make it variable according to the value of the immediately preceding binarization threshold value Dsh. In this case, as shown in FIG. 14A, when the hand outline Eg is not detected in S108 (S108; NO), the process shown in FIG. 14B is executed.

  In addition, the control process concerning the search of the binarization threshold value described in FIGS. 14A and 14B is an example of the process described in claim 3. Moreover, the process concerning S407 of FIG. 14 is an example of the process of Claim 5.

FIG. 14A is a flowchart showing only the process near the changed portion in the process shown in FIG. In FIG. 14B, the binarization threshold Dsh is the binarization threshold Dsh used when it is determined NO in S108 (hereinafter, this binarization threshold is particularly referred to as “immediate binarization threshold”). 5 is a flowchart when searching in a narrow range based on the above. 14A and 14B is executed by the function of the object detection unit 31a of the CPU 31 of the information processing apparatus 3 as in FIGS.

  Referring to FIG. 14B, when the hand outline Eg is not detected (S108: NO), the CPU 31 adds ΔDm corresponding to a predetermined distance to the immediately preceding binarization threshold Dsh (S401). Then, the CPU 31 generates a binarized image Mi using the binarization threshold Dsh set in S401 (S402), and determines whether the hand outline Eg can be detected based on the generated binarized image Mi. If the hand outline Eg cannot be detected (S403, S404), the binarization threshold Dsh is decreased by ΔD until the hand outline Eg is detected (S404: YES) (S405). When the hand outline Eg is not detected (S404: NO), the CPU 31 determines whether or not the binarization threshold Dsh is lower than the threshold Dsm4 (S406). The threshold value Dsm4 is set to a value corresponding to a position corresponding to a distance from the position corresponding to the previous binarization threshold value Dsh by a predetermined distance. Thereby, as shown in FIG. 14C, the binarization threshold value Dsh is searched so as to gradually move away from the previous position to the threshold value Dsm4 by a predetermined distance from the previous binarization threshold value Dsh.

  As described above, in the process of FIG. 14B, the search for the binarization threshold value Dsh can be limited to a narrow range, so that the amount of calculation can be suppressed lower than that in the above embodiment.

  When the contour Eg of the hand is detected by this search (S404: YES), the CPU 31 subtracts ΔDo from the binarization threshold Dsh at that time and binarization threshold used for contour detection as in the above embodiment. Dsh is set (S407).

  When the binarization threshold value Dsh is not found by the position corresponding to the threshold value Dsm4 (S406: YES), the CPU 31 advances the process to S201 in FIG. 9 and again in the wide range corresponding to D0 to Dsm. Dsh is searched. Therefore, the detection accuracy of the binarization threshold value Dsh can be maintained. Also, since the distance of an object usually changes so as to gradually move away from the original position as time elapses, it is difficult to perform a search in a wide range corresponding to D0 to Dsm, and binarization is performed. It is assumed that the amount of calculation required for searching for the threshold value Dsh can be kept low.

  In the above embodiment and the modified example, the binarization threshold Dsh is searched while shifting from a short distance to a value corresponding to a long distance, but while shifting from a long distance to a value corresponding to a short distance, The binarized threshold value Dsh may be searched.

  In the above embodiment, the segment areas are set so that the adjacent segment areas overlap each other, but the segment areas may be set so that the segment areas adjacent to the left and right do not overlap each other. The segment areas may be set so that the segment areas adjacent in the vertical direction do not overlap each other. Further, the shift amount of the segment areas adjacent in the vertical and horizontal directions is not limited to one pixel, and the shift amount may be set to another number of pixels. Moreover, in the said embodiment, although the magnitude | size of the segment area | region was set to horizontal 15 pixels x vertical 15 pixels, it can set arbitrarily according to detection accuracy. Furthermore, in the said embodiment, although the segment area | region was set to square shape, a rectangle may be sufficient.

In the above embodiment, the pixel values of the pixels included in the segment area and the comparison area are binarized before calculating the matching rate between the segment area and the comparison area. Matching may be performed using the values as they are. In the above embodiment, the pixel value obtained by the CMOS image sensor 240 is binarized as it is. However, the pixel value is subjected to correction processing such as predetermined pixel weighting processing and background light removal processing. After performing, it may be binarized or multi-valued.

  Further, in the above embodiment, the distance information is obtained using the triangulation method and stored in the memory 25. However, when the object contour extraction is mainly intended, the distance using the triangulation method is calculated. The displacement amount (pixel displacement amount) of the segment area may be acquired as the distance information without calculating.

  Further, in the above embodiment, the filter 230 is disposed to remove light in a wavelength band other than the wavelength band of the laser light irradiated to the target region. For example, light other than the laser light irradiated to the target region is used. In the case where a circuit configuration for removing the signal component is removed from the signal output from the CMOS image sensor 240, the filter 230 can be omitted. Further, the arrangement position of the aperture 210 may be between any two imaging lenses.

  In the above embodiment, the CMOS image sensor 240 is used as the light receiving element, but a CCD image sensor may be used instead. Furthermore, the configurations of the projection optical system 100 and the light receiving optical system 200 can be changed as appropriate.

  The embodiments of the present invention can be appropriately modified in various ways within the scope of the technical idea shown in the claims.

1 ... Object detection device
2 ... Information acquisition device (information acquisition unit)
21 ... CPU (information acquisition unit, distance acquisition unit)
21b ... Distance acquisition unit (information acquisition unit)
21c ... Object detection unit 23 ... Imaging signal processing circuit (information acquisition unit, distance acquisition unit)
25 ... Memory (information acquisition unit, storage unit)
3 ... Information processing device (object detection unit)
31 ... CPU (object detection unit)
31a ... Object detection unit 100 ... Projection optical system (information acquisition unit)
110 ... Laser light source (information acquisition unit)
200 ... Light receiving optical system (information acquisition unit)
240 ... CMOS image sensor (information acquisition unit, image sensor)
S1 to Sn: Segment area (reference area)
Dsh: Binary threshold (threshold)
Mi ... Binary image (binarization information)

Claims (6)

In an object detection device that detects an object from a target area,
An information acquisition unit for acquiring three-dimensional distance information related to the distance to each reference position set in the target area;
By comparing the distance to each reference position obtained from the three-dimensional distance information with a predetermined threshold value, binary information is generated by binarizing the distance at each reference position, and the binary An object detection unit for detecting the shape of the object from the conversion information,
The object detection unit changes the threshold according to a change in distance to an object to be detected.
An object detection apparatus characterized by that. The object detection apparatus according to claim 1,
The object detection unit executes the search for the threshold that can detect the object to be detected while changing the threshold within a predetermined range at the start of an object detection operation.
An object detection apparatus characterized by that. In the object detection device according to claim 1 or 2,
When the object detection unit cannot detect the detection target object from the binarized information during the object detection operation, the object detection unit detects the object while changing the threshold value within a predetermined range. Perform a search,
An object detection apparatus characterized by that. In the object detection device according to claim 2 or 3,
In the search for the threshold, the object detection unit searches for a first threshold that can detect an object related to the object to be detected, and then within a predetermined range from the first threshold, Searching for a second threshold capable of detecting the object to be detected, and setting the threshold for the object to be detected based on the searched second threshold;
An object detection apparatus characterized by that. In the object detection device according to any one of claims 2 to 4,
In the search for the threshold value, the object detection unit offsets the position corresponding to the threshold value when the object to be detected becomes detectable in a direction away from the object detection device by a predetermined distance. Setting a value for a position to the threshold for detecting the object;
An object detection apparatus characterized by that. In the object detection device according to any one of claims 1 to 5,
The information acquisition unit
A projection optical system that projects laser light emitted from a laser light source onto a target area with a predetermined dot pattern;
A light receiving optical system that is arranged so as to be laterally separated by a predetermined distance with respect to the projection optical system, and that captures the target area by an image sensor;
A storage unit that holds reference information based on a reference dot pattern imaged by the light receiving optical system when the laser beam is irradiated on a reference surface;
The reference area allocated to the reference dot pattern is moved on the measured dot pattern in a predetermined search range by referring to the measured information based on the measured dot pattern imaged by the image sensor at the time of actual measurement and the reference information. A distance acquisition unit that executes a position search and acquires distance information with respect to the reference region based on the searched movement position.
An object detection apparatus characterized by that.