CN112837381A - Camera calibration method, system and equipment suitable for driving equipment - Google Patents
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Abstract
The invention discloses a method for calibrating a camera suitable for driving equipment, which comprises the following steps: carrying out external reference calibration on the camera when the driving equipment is in a first load state to obtain first calibration information, wherein the first calibration information comprises a first coordinate conversion relation between a navigation environment coordinate system and a camera coordinate system in the first load state; performing external reference calibration on the camera when the driving equipment is in a second load state to obtain second calibration information, wherein the second calibration information comprises a second coordinate conversion relation between a navigation environment coordinate system and a camera coordinate system in the second load state, and the loads in the first load state and the second load state are different; and obtaining the self-adaptive external parameters of the camera according to the first calibration information and the second calibration information. By adopting the technical scheme, the positioning precision of the camera is improved. The invention also provides a calibration system and a calculation device of the camera suitable for the driving device.
Description
Technical Field
The invention relates to the technical field of driving equipment, in particular to a method, a system and equipment for calibrating a camera suitable for driving equipment.
Background
At present, in the field of driving equipment, particularly automatic driving equipment such as an automatic driving vehicle, a camera for detecting a positioning marker for navigation is often required to be mounted afterwards. Therefore, calibration of relevant external parameters is required to be performed on the camera, a coordinate transformation relationship between a camera coordinate system of the camera and a vehicle body coordinate system and a coordinate transformation relationship between the camera coordinate system and a navigation environment coordinate system (i.e., a world coordinate system) are obtained, and the coordinate transformation relationship between the camera coordinate system and the vehicle body coordinate system is further obtained, so that a coordinate of an object shot by the camera in the navigation environment coordinate system and a relative position relationship between the object and the vehicle body can be obtained.
Disclosure of Invention
The applicant finds that in the prior art, the problem of large positioning error exists in the use process after the camera of the driving equipment is calibrated. The applicant further studies and finds that the calibration of the coordinate transformation relation between the camera coordinate system and the navigation environment coordinate system is a very important loop in the whole calibration process, and the influence of the load on the external reference of the camera is not considered when the calibration between the camera coordinate system and the navigation environment coordinate system is carried out on the camera in the prior art. The applicant finds that the external parameter of the camera obviously changes along with different loading conditions of the driving equipment, once the loading conditions change, obvious errors occur in the coordinate conversion relation between coordinate systems obtained by calibration in a single loading state and the actual coordinate conversion relation, and further larger positioning errors are generated in the using process.
The invention aims to solve the problem that a camera of driving equipment in the prior art has large positioning error in the use process.
In order to solve the technical problem, the embodiment of the invention discloses a calibration method of a camera suitable for a driving device, which comprises the following steps: carrying out external reference calibration on the camera when the driving equipment is in a first load state to obtain first calibration information, wherein the first calibration information comprises a first coordinate conversion relation between a navigation environment coordinate system and a camera coordinate system in the first load state; performing external reference calibration on the camera when the driving equipment is in a second load state to obtain second calibration information, wherein the second calibration information comprises a second coordinate conversion relation between a navigation environment coordinate system and a camera coordinate system in the second load state, and the loads in the first load state and the second load state are different; and obtaining the self-adaptive external parameters of the camera according to the first calibration information and the second calibration information, wherein the self-adaptive external parameters comprise self-adaptive coordinate conversion relation between a navigation environment coordinate system and a camera coordinate system.
By adopting the technical scheme, the positioning precision of the camera is improved.
Optionally, the first load state is an unloaded state and the second load state is a fully loaded state.
Optionally, the external reference calibration comprises static external reference calibration and dynamic external reference calibration.
Optionally, the camera is a binocular camera, and the static external reference calibration includes the following steps: controlling the driving equipment to run to a static calibration area, wherein the static calibration area is provided with a first marker; the camera collects images of a first marker of the driving equipment in a static state; obtaining the image coordinates of a first characteristic point of the first marker according to the image of the first marker; and obtaining static external parameters of the camera according to the image coordinates of the first characteristic point, the internal reference data of the camera and the coordinates of the first characteristic point in the navigation environment coordinate system, wherein the static external parameters comprise a static conversion relation between the navigation environment coordinate system and the camera coordinate system.
Alternatively, the step of obtaining the image coordinates of the first feature point of the first marker from the image of the first marker includes: converting the color of the image of the first marker to an HSV color space; filtering the converted image in an HSV color space; inputting the filtered image into a recognizer of a deep learning model; and obtaining the image coordinates of the first characteristic point according to the output result of the recognizer.
Optionally, the first marker comprises at least 3L-shaped painted markers.
Optionally, the dynamic external reference calibration comprises the following steps: controlling the driving equipment to run to a dynamic calibration area, wherein the dynamic calibration area is provided with a second marker; the camera collects images of a second marker in a driving state of the driving equipment; and obtaining dynamic external parameters of the camera according to the image of the second marker and the static external parameters, wherein the dynamic external parameters comprise a dynamic conversion relation between a navigation environment coordinate system and a camera coordinate system.
Optionally, the second marker includes two dynamic calibration lane lines that are respectively disposed on the left and right sides of the driving device and are parallel to each other, and the step of obtaining the dynamic external reference parameter of the camera according to the image of the second marker and the static external reference parameter includes: obtaining vanishing point information of the dynamic calibration lane line according to the image of the second marker; and obtaining the dynamic external parameter according to the static external parameter and the vanishing point information.
Optionally, the first calibration information and the second calibration information include dynamic external parameters of the driving device in a corresponding load state, and the step of obtaining the adaptive external parameters of the camera according to the first calibration information and the second calibration information includes: obtaining a vanishing point change model according to dynamic external parameters of the driving equipment in different load states; and fitting according to the vanishing point change model to obtain the self-adaptive external parameters of the camera.
Optionally, the calibration method further comprises the following steps: obtaining vanishing point deviation data according to vanishing point information of the driving equipment in different load states; and verifying the accuracy of the dynamic external parameter according to the vanishing point deviation data.
Optionally, the dynamic calibration lane line is provided with auxiliary short lines at preset intervals.
Optionally, the driving device is an automatic driving device, and cameras are mounted at the front end and the rear end of the automatic driving device.
The embodiment of the invention also discloses a calibration system of the camera suitable for the driving equipment, which comprises the following components: the static calibration area is provided with a first marker and is used for carrying out static external reference calibration on the camera; the dynamic calibration area is provided with a second marker and is used for carrying out dynamic external reference calibration on the camera; the calibration system calibrates the camera by using the calibration method in the foregoing embodiment.
The embodiment of the invention also discloses a computing device, which comprises: a processor adapted to implement various instructions; a memory adapted to store a plurality of instructions adapted to be loaded by the processor and to perform any of the calibration methods described above.
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FIG. 1 is a flow chart illustrating a method for scaling in accordance with an embodiment of the present invention;
FIG. 2 is a schematic diagram of a static calibration zone in accordance with an embodiment of the present invention;
FIG. 3 is a schematic diagram of a dynamic calibration zone in an embodiment of the present invention;
FIG. 4 shows a schematic view of a static calibration zone in a further embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention is provided for illustrative purposes, and other advantages and effects of the present invention will become apparent to those skilled in the art from the present disclosure. While the invention will be described in conjunction with the preferred embodiments, it is not intended that features of the invention be limited to these embodiments. On the contrary, the invention is described in connection with the embodiments for the purpose of covering alternatives or modifications that may be extended based on the claims of the present invention. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. The invention may be practiced without these particulars. Moreover, some of the specific details have been left out of the description in order to avoid obscuring or obscuring the focus of the present invention. It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
It should be noted that in this specification, like reference numerals and letters refer to like items in the following drawings, and thus, once an item is defined in one drawing, it need not be further defined and explained in subsequent drawings.
In the description of the embodiments of the present invention, it should be noted that the terms "upper", "lower", "inner", "bottom", and the like, indicate orientations or coordinate relationships based on the orientations or coordinate relationships shown in the drawings or orientations or coordinate relationships conventionally arranged in use of products of the present invention, and are only used for convenience in describing the present invention and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present invention.
The terms "first," "second," and the like are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance.
In the description of the embodiments of the present invention, it should be further noted that unless otherwise explicitly stated or limited, the terms "disposed," "connected," and "connected" are to be construed broadly and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present embodiment can be understood in specific cases by those of ordinary skill in the art.
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail with reference to the accompanying drawings.
Referring to fig. 1 to 3, an embodiment of the present invention discloses a calibration method for a camera suitable for a driving device, including the following steps: s1: carrying out external reference calibration on the camera when the driving equipment is in a first load state to obtain first calibration information, wherein the first calibration information comprises a first coordinate conversion relation between a navigation environment coordinate system and a camera coordinate system in the first load state; s2: performing external reference calibration on the camera when the driving equipment is in a second load state to obtain second calibration information, wherein the second calibration information comprises a second coordinate conversion relation between a navigation environment coordinate system and a camera coordinate system in the second load state, and the loads in the first load state and the second load state are different; s3: and obtaining the self-adaptive external parameters of the camera according to the first calibration information and the second calibration information, wherein the self-adaptive external parameters comprise self-adaptive coordinate conversion relation between a navigation environment coordinate system and a camera coordinate system.
In the present embodiment, the driving apparatus is mounted with a camera. In S1-S2, by performing external reference calibration on the cameras of the driving device in different load states, the first calibration information and the second calibration information can be obtained respectively, that is, the coordinate conversion relationship between the navigation environment coordinate system and the camera coordinate system in different load states can be obtained. In S3, obtaining adaptive external parameters of the camera according to the first calibration information and the second calibration information, where the adaptive external parameters include an adaptive coordinate transformation relationship between a navigation environment coordinate system and a camera coordinate system. That is, the adaptive external reference in the present embodiment includes a coordinate conversion relationship between the navigation environment coordinate system and the camera coordinate system that can dynamically change depending on the load. The adaptive external parameters obtained by the calibration method of the embodiment can be combined with the coordinate conversion relationship between the navigation environment coordinate system and the vehicle body coordinate system to obtain the dynamic coordinate conversion relationship between the camera coordinate system and the vehicle body coordinate system, so that the complete calibration of the camera is completed. Therefore, the calibration method disclosed by the embodiment fully considers the influence of different loads of the driving equipment on the camera external parameter, and can meet the requirement of one-time overall calibration of the camera external parameter for multiple times. The change of camera external parameters caused by the conditions such as the change of tires due to different loads and the change of the position of the camera is avoided, the coordinate conversion relation obtained by calibration can be more accurate and is closer to the actual coordinate conversion relation of the driving equipment in the use state, and the positioning precision of the camera is high.
It can be understood that the calibration of the coordinate transformation relationship between the navigation environment coordinate system and the vehicle body coordinate system can be realized by means of instrument measurement, such as total station measurement, and the embodiment does not limit the same. The specific method for obtaining the adaptive external parameter of the camera according to the first calibration information and the second calibration information may be data modeling, data fitting, and the like, for example, linear fitting, nonlinear fitting, and the like, which is not limited in this embodiment. In this embodiment, there are various specific implementation methods for external reference calibration. For example, the coordinates under the navigation coordinate system of a plurality of markers may be measured respectively, and the transformation relationship between the two coordinate systems, such as the rotation matrix and the translation matrix between the two coordinate systems, may be obtained by solving the coordinates under the camera coordinate system obtained by combining the images of the markers captured by the camera; or the coordinates of a marker in navigation coordinate systems at different positions are respectively measured, and the coordinates in a camera coordinate system are obtained by combining the images of the markers shot by the camera, so that the conversion relation between the two coordinate systems is obtained; other methods are also possible, and this embodiment is not limited thereto.
By adopting the technical scheme, the positioning precision of the camera is improved.
The invention further discloses a calibration method of a camera suitable for driving equipment, wherein the first load state is an unloaded state, and the second load state is a fully loaded state. In the present embodiment, the first load state is set to the no-load state, and the second load state is set to the full-load state, so that the coordinate conversion relationship between the camera coordinate system and the navigation environment coordinate system can be obtained when the driving device is in the two extreme load states. The coordinate conversion relation between the two coordinate systems when the driving equipment is in each middle load state can be accurately obtained through the first calibration information and the second calibration information, and the accuracy of the self-adaptive external parameters can be further improved. The calibration under twice extreme loads not only has higher calibration precision, but also effectively reduces the error accumulation phenomenon in the repeated calibration process and ensures the system precision. In one embodiment, the driving device is a vehicle with a rated load of 64 tons, and coordinate transformation relations between a camera coordinate system and a navigation environment coordinate system of the vehicle in states of 0 ton load and 64 tons load are respectively obtained, so as to obtain an adaptive external parameter of the vehicle corresponding to dynamic changes between 0 and 64 tons. In other embodiments, the nominal load of the steering device may also be other values.
The invention further discloses a calibration method of the camera suitable for the driving equipment. That is to say, in the calibration method disclosed in this embodiment, static external reference calibration and dynamic external reference calibration are performed on the camera of the driving device in the first load state, and static external reference calibration and dynamic external reference calibration are also performed on the camera of the driving device in the second load state, so as to obtain corresponding calibration information. The adaptive external parameter obtained by the calibration method disclosed by the embodiment fully considers the influence of the motion state on the external parameter of the camera, so that the calibration result is more accurate, and the positioning precision of the camera is further improved.
Referring to fig. 2, another embodiment of the present invention discloses a calibration method for a camera suitable for a driving device, where the camera 11 is a binocular camera, and the static external reference calibration includes the following steps: controlling the driving equipment 1 to run to a static calibration area, wherein the static calibration area is provided with a first marker 2; the camera 11 collects images of the first marker 2 of the driving equipment 1 in a static state; obtaining the image coordinates of the first characteristic point of the first marker 2 according to the image of the first marker 2; and obtaining static external parameters of the camera 11 according to the image coordinates of the first characteristic point, the internal reference data of the camera 11 and the coordinates of the first characteristic point in the navigation environment coordinate system, wherein the static external parameters comprise a static conversion relation between the navigation environment coordinate system and the camera coordinate system.
In the present embodiment, the camera 11 is a binocular camera, and the binocular camera can determine the distance through parallax calculation of images, does not need frequent maintenance, and is more suitable for complex scenes, automatic driving, and the like. In the present embodiment, first, the driving apparatus 1 is controlled to travel until the first target is setAnd (3) a static calibration area of the object 2, wherein the design of the static calibration area is completed before static external reference calibration is carried out. Then, the camera 11 shoots and collects the image of the first marker 2 of the driving equipment in a static state; next, the image coordinates of the first feature point of the first marker 2 are obtained from the image of the first marker 2, and the first feature point may be determined according to the shape, color, and the like of the marker. Then, the coordinates of the first feature point in the camera coordinate system may be obtained by combining the imaging principle of the binocular camera, for example, using an isometric projection model to perform back projection according to the image coordinates of the first feature point and the internal reference data of the camera 11. The internal reference data of the camera can comprise focal length, principal point, distortion information and the like, and can be obtained in advance or at the time. Optionally, the distortion information comprises a radial distortion coefficient and a tangential distortion coefficient. Then, combining the coordinates of the first characteristic point in the camera coordinate system with the coordinates of the first characteristic point in the navigation environment coordinate system, the static external parameters of the binocular camera as a whole can be obtained through solving, wherein the static external parameters comprise a static conversion relation between the navigation environment coordinate system and the camera coordinate system. The coordinates of the first feature point in the navigation environment coordinate system may be obtained by measurement using a measuring instrument such as the total station 3, as long as the coordinates are obtained before the static external parameters are solved. According to the embodiment, the fixed target is arranged in the calibration area, and the image acquired by the binocular camera and the coordinate of the navigation environment coordinate system measured by the measuring instrument are combined, so that the calibration result can be automatically calculated. In one embodiment, let the coordinate of the first feature point in the camera coordinate system be XcThe coordinate in the navigation environment coordinate system is Xd，Xd＝R1Xc+T1，R1For rotating matrix coefficients, T1For shifting matrix coefficients, substituting XcAnd XdIs solved to obtain R1And T1And obtaining the static conversion relation between the two navigation environment coordinate systems and the camera coordinate system.
The invention further discloses a calibration method of a camera suitable for driving equipment, which comprises the following steps of obtaining image coordinates of a first characteristic point of a first marker 2 according to an image of the first marker 2, wherein the method comprises the following steps: converting the color of the image of the first marker 2 to HSV color space; filtering the converted image in an HSV color space; inputting the filtered image into a recognizer of a deep learning model; and obtaining the image coordinates of the first characteristic point according to the output result of the recognizer.
In the present embodiment, the image of the first marker 2 captured by the camera 11 is converted into HSV color space. Information such as the chroma, the saturation, the brightness and the like of each pixel can be extracted to be stored, the HSV space can more visually express the brightness, the hue and the brightness of colors, the contrast between colors is convenient to carry out, and the first marker 2 is highlighted. And then, filtering the converted image in an HSV color space. In one embodiment, the threshold range of each color saturation and the threshold range of each color saturation are counted, threshold extraction is performed by using a watershed algorithm, and filtering processing is performed on the image. In other embodiments, other image filtering methods may be employed. Then, the filtered image is input to a recognizer of the deep learning model, and the first feature point is recognized. And finally, obtaining the image coordinates of the first characteristic point according to the output result of the recognizer. The recognizer of the deep learning model can be obtained by training in advance before calibration or can be obtained by training images in the calibration process. The deep learning model can realize a set of automatic feature point identification through a deep learning network, automatically matches a search strategy of feature point image coordinate position information, and greatly improves the accuracy of feature point identification by applying computer vision and deep learning to the processing of marker images. Preferably, the deep learning network system defaults to the existence of the feature point of the first marker only in the image collected by the binocular camera and used for basic static external reference calibration. In an embodiment, on the filtered image, modeling training is performed on the first feature point, a deep learning network is input, the first feature point is calculated, and then a reverse neural network model with strong robustness is obtained and used as a recognizer for accurately recognizing the feature point. And the deep learning network is used for identifying the feature points, so that the efficiency is high and the accuracy is higher compared with manual processing.
Preferably, the ROI (region of interest) extraction preprocessing is performed on the image of the first marker 2 before the image is converted into the HSV color space, which can reduce the subsequent data processing amount. Preferably, the color of the first marker 2 is white, which can enhance the contrast between the first marker 2 and the background, such as the road, and improve the accuracy of identification.
Referring to fig. 2, another embodiment of the invention discloses a calibration method for a camera suitable for a driving device, and the first marker 2 comprises at least 3L-shaped painting markers. In this embodiment, the first marker 2 includes at least 3L-shaped coating markers, the angular point 21 of each L-shaped marker is more obvious in the image, and the angular point 21 is used as a first feature point, so that the identification is convenient, and the accuracy is high. The coating mode can avoid the displacement of the mark and the influence on calibration. The method has the advantages that at least three markers are arranged at one time, so that the static external reference parameters can be calibrated conveniently by shooting and taking images at one time, and the markers do not need to be moved for taking images for multiple times. Preferably, the static calibration area is provided with 8L-shaped identifications within the shooting range of the camera 11, every 4 identifications are a group, the two groups are arranged in parallel, the design is convenient, each camera in the binocular camera can shoot 8 identifications simultaneously, the obtained static external parameters are verified and converged by using 8 groups of data, and the optimal solution is obtained. The size and the interval of the L-shaped marks may be set as needed, but the present embodiment does not limit this. In one embodiment, the L-shaped marks have dimensions of 50cm by 50cm, and the spacing between adjacent marks in a group is 1.5 meters.
Preferably, the static calibration area is provided with a static calibration lane line 4, the first feature point of the identifier in each group of the first marker 2 is located at the equal-width distance position on the static calibration lane line 4, so that the calibration and the daily work detection can share one set of data, and the actual operation efficiency is greatly improved. Preferably, in the vertical direction (the X direction is shown in fig. 2), the first characteristic point of each first marker is on the static calibration lane line 4. Preferably, the static calibration area is further provided with a stop sign 5, and the position of the stop sign 5 is determined according to the distance between the tires of the driving device 1, so that the first marker 2 is ensured to appear in the visual field of the camera 11 after accurate parking, and the calibration efficiency is improved. Preferably, the lane formed between the two sets of markers is also provided with a lane center dashed line 6 for assisting parking.
Referring to fig. 3, another embodiment of the present invention discloses a calibration method for a camera of a driving device, where the dynamic external reference calibration includes the following steps: controlling the driving equipment 1 to run to a dynamic calibration area, wherein the dynamic calibration area is provided with a second marker 7; the camera 11 collects images of the second marker 7 in the driving state of the driving equipment 1; and obtaining the dynamic external parameters of the camera 11 according to the image of the second marker 7 and the static external parameters, wherein the dynamic external parameters comprise a dynamic conversion relation between a navigation environment coordinate system and a camera coordinate system. In the present embodiment, when performing dynamic external reference calibration, the camera 11 acquires an image of the second marker 7 in the driving state of the driving device 1, and then obtains a dynamic external reference parameter of the camera 11 by combining the static external reference parameter obtained by static external reference calibration. That is to say, in the present embodiment, the static external parameter is corrected based on the static external parameter in combination with the image information of the second marker 7 when the driving device 1 moves, so as to obtain the dynamic external parameter, thereby further improving the precision and efficiency of calibration. That is, in the present embodiment, the first coordinate conversion relationship includes the dynamic external reference parameter in the first load state, and the second coordinate conversion relationship includes the dynamic external reference parameter in the second load state. The coordinates of the second marker 7 in the navigation environment coordinate system can be obtained by measuring with an instrument such as a total station, or by setting an auxiliary marker.
Referring to fig. 3, another embodiment of the present invention discloses a calibration method for a camera of a driving device, where a second marker 7 includes two dynamic calibration lane lines 71 that are respectively disposed on the left and right sides of the driving device 1 and are parallel to each other, and a step of obtaining a dynamic external parameter of the camera 11 according to an image and a static external parameter of the second marker 7 includes: obtaining vanishing point information of the dynamic calibration lane line 71 according to the image of the second marker 7; and obtaining the dynamic external parameter according to the static external parameter and the vanishing point information. In this embodiment, two practically parallel dynamic calibration lane lines 71 are set, and at this time, the image captured by the camera 11 includes the two dynamic calibration lane lines 71, so that the lane lines can be identified according to the image and the coordinates of vanishing points of the lane where the driving device 1 is located in the perspective projection can be calculated, where the vanishing points are far away from the image or intersection points where the two dynamic calibration lane lines 71 may extend to. Therefore, the vanishing point information of the dynamic calibration lane line 71, such as the coordinates of the vanishing point, can be obtained according to the image of the dynamic calibration lane line 71, and then the corresponding dynamic external parameter can be obtained after correction by combining the static external parameter obtained before. According to the calibration method disclosed by the embodiment, in the operation process of the driving equipment 1 and under the condition of different loads of the driving equipment 1, the binocular camera dynamically corrects the external parameters by continuously updating and identifying the dynamic calibration lane line 71, so that the current external parameters are matched with the current load condition, the calibration method not only has higher calibration precision, but also effectively reduces the error accumulation phenomenon in the repeated calibration process, and ensures the system precision. And dynamic external parameter calibration can be conveniently and rapidly completed, calibration efficiency is improved, and calibration cost is reduced. In some embodiments, the driving device 1 collects images of the dynamic calibration lane line 71 at a certain frequency during the traveling of the dynamic calibration area, and performs adaptive dynamic calibration.
The invention further discloses a calibration method of a camera suitable for a driving device, wherein the first calibration information and the second calibration information comprise dynamic external parameters of the driving device 1 in a corresponding load state, and the step of obtaining the self-adaptive external parameters of the camera 11 according to the first calibration information and the second calibration information comprises the following steps: obtaining a vanishing point change model according to dynamic external parameters of the driving equipment 1 in different load states; and fitting according to the vanishing point change model to obtain the self-adaptive external parameters of the camera 11. In the present embodiment, it is considered that the vanishing points of the dynamic calibration line may be deviated in different load states, and correspondingly, the dynamic external parameters may be changed in different load states. In one embodiment, let us say that the coordinates of the object in the camera coordinate system are X when the driving device 1 is in the first load stateaIn navigation ofThe coordinate in the environment coordinate system is XbWherein X isb＝RaXa+Ta，RaFor rotating matrix coefficients, TaThe dynamic external parameters being coefficients of a translation matrix, i.e. the first load state, include RaAnd TaIf the coordinate transformation relationship under the second load state is Xb＝Ra(R△+T△)Xa+TbAnd the coordinate conversion relation in the second load state can also be obtained according to the dynamic external parameter obtained by correcting the static external parameter in the second load state. R can thus be solved△And T△And a corresponding vanishing point change model is established, and then the adaptive appearance parameters of the camera 11 under different loads, namely the dynamic coordinate conversion relation between the navigation environment coordinate system and the camera coordinate system under different loads, are obtained according to the vanishing point change model. The data fitting is carried out by a model establishing method, so that the efficiency and the accuracy can be improved.
The invention discloses a calibration method of a camera suitable for driving equipment, which further comprises the following steps: obtaining vanishing point deviation data according to vanishing point information of the driving equipment 1 in different load states; and verifying the accuracy of the dynamic external parameter according to the vanishing point deviation data. In the present embodiment, the offset data of the vanishing points is obtained from the vanishing point information under different loads, and for example, when the vanishing point information includes vanishing point coordinates, the offset data may be a coordinate difference. It can be understood that the dynamic external parameters in the first load state and the second load state are obtained by combining the static external parameters in the corresponding states with the vanishing point information in the foregoing process. In addition, the dynamic external parameters in the second load state may be obtained by combining the dynamic external parameters in the first load state with the vanishing point deviation data. Therefore, in the present embodiment, it is possible to verify whether the dynamic external parameters in different load states are accurate or not by the vanishing point deviation data.
Referring to fig. 3, in another embodiment of the present invention, a calibration method for a camera of a driving device is disclosed, in which an auxiliary short line 72 with a preset interval is disposed on a dynamic calibration lane line 71. In the present embodiment, the auxiliary short line 72 is provided, so that the actual distance between the vanishing point and the camera 11 can be obtained, and the image coordinates of the vanishing point in the perspective projection image can be accurately obtained in combination with the image captured by the camera 11, so that data verification can be performed. It will be appreciated that the spacing and size of the secondary stubs 72 can be set as desired. In one embodiment, the lane width formed between the two dynamic calibration lane lines 71 is 4.2 meters, the line width of the dynamic calibration lane line 71 is 15cm, a set of auxiliary short lines 72 with the length of 15cm and the width of 5cm are respectively drawn on the inner sides of the two dynamic calibration lane lines 71, and the interval between the auxiliary short lines 72 is 20 cm.
Referring to fig. 4, another embodiment of the present invention discloses a calibration method for a camera suitable for a driving device, where the driving device 1 is an automatic driving device, and the front and rear ends of the automatic driving device are both provided with cameras 11. In the present embodiment, the driving device 1 is an automatic driving device, and cameras 11 for detecting and navigating the positioning markers are mounted on both the front and rear ends. When the calibration method disclosed by the embodiment is applied to calibration of the camera 11 of the automatic driving equipment, the GPS system of the automatic driving equipment can realize convenient and fast automatic calibration, reduce errors caused by uncertain environmental factors and uncertain manual operation in the calibration process, and improve the precision and efficiency of the calibration system. In an embodiment, the design of the static calibration area can be as shown in fig. 4, and the calibration of the front and rear cameras 11 can be completed simultaneously.
Referring to fig. 2 to 3, an embodiment of the present invention further discloses a calibration system for a camera of a driving device, including: the static calibration area is provided with a first marker 2 and is used for carrying out static external reference calibration on the camera 11; the dynamic calibration area is provided with a second marker 7 and is used for carrying out dynamic external reference calibration on the camera 11; the calibration system calibrates the camera by using the calibration method in the foregoing embodiment. With reference to the calibration method in the foregoing embodiment, the calibration system disclosed in this embodiment can improve the calibration accuracy and efficiency, thereby improving the positioning accuracy of the camera in the subsequent use process.
The embodiment of the invention also discloses a computing device, which comprises: a processor adapted to implement various instructions; a memory adapted to store a plurality of instructions, the instructions adapted to be loaded by the processor and to perform the calibration method of any of the preceding embodiments.
The embodiments disclosed herein may be implemented in hardware, software, firmware, or a combination of these implementations. Embodiments of the application may be implemented as computer programs or program code executing on programmable systems comprising at least one processor, a storage system (including volatile and non-volatile memory and/or storage elements), at least one input device, and at least one output device. Program code may be applied to input instructions to perform the functions described herein and generate output information. The output information may be applied to one or more output devices in a known manner. For purposes of this application, a processing system includes any system having a processor such as, for example, a Digital Signal Processor (DSP), a microcontroller, an Application Specific Integrated Circuit (ASIC), or a microprocessor.
In some cases, the disclosed embodiments may be implemented in hardware, firmware, software, or any combination thereof. The disclosed embodiments may also be implemented as instructions carried by or stored on one or more transitory or non-transitory machine-readable (e.g., computer-readable) storage media, which may be read and executed by one or more processors. For example, the instructions may be distributed via a network or via other computer readable media. Thus, a machine-readable medium may include any mechanism for storing or transmitting information in a form readable by a machine (e.g., a computer), including, but not limited to, floppy diskettes, optical disks, read-only memories (CD-ROMs), magneto-optical disks, read-only memories (ROMs), Random Access Memories (RAMs), erasable programmable read-only memories (EPROMs), electrically erasable programmable read-only memories (EEPROMs), magnetic or optical cards, flash memory, or a tangible machine-readable memory for transmitting information (e.g., carrier waves, infrared digital signals, etc.) using the internet in an electrical, optical, acoustical or other form of propagated signal. Thus, a machine-readable medium includes any type of machine-readable medium suitable for storing or transmitting electronic instructions or information in a form readable by a machine (e.g., a computer).
In the drawings, some features of the structures or methods may be shown in a particular arrangement and/or order. However, it is to be understood that such specific arrangement and/or ordering may not be required. Rather, in some embodiments, the features may be arranged in a manner and/or order different from that shown in the illustrative figures. In addition, the inclusion of a structural or methodical feature in a particular figure is not meant to imply that such feature is required in all embodiments, and in some embodiments, may not be included or may be combined with other features.
While the invention has been shown and described with reference to certain preferred embodiments thereof, it will be understood by those skilled in the art that the foregoing is a more detailed description of the invention, taken in conjunction with the specific embodiments thereof, and that no limitation of the invention is intended thereby. Various changes in form and detail, including simple deductions or substitutions, may be made by those skilled in the art without departing from the spirit and scope of the invention.
Claims (14)
1. A calibration method for a camera suitable for a driving device is characterized by comprising the following steps:
carrying out external reference calibration on the camera when the driving equipment is in a first load state to obtain first calibration information, wherein the first calibration information comprises a first coordinate conversion relation between a navigation environment coordinate system and a camera coordinate system in the first load state;
performing the external reference calibration on the camera when the driving equipment is in a second load state to obtain second calibration information, wherein the second calibration information comprises a second coordinate conversion relation between the navigation environment coordinate system and the camera coordinate system in the second load state, and the first load state and the second load state have different loads;
and obtaining the self-adaptive external parameters of the camera according to the first calibration information and the second calibration information, wherein the self-adaptive external parameters comprise self-adaptive coordinate conversion relation between the navigation environment coordinate system and the camera coordinate system.
2. The calibration method according to claim 1, wherein the first load state is an unloaded state and the second load state is a fully loaded state.
3. The calibration method according to claim 1, wherein the external reference calibration comprises a static external reference calibration and a dynamic external reference calibration.
4. The calibration method according to claim 3, wherein the camera is a binocular camera, and the static external reference calibration comprises the following steps:
controlling the driving equipment to run to a static calibration area, wherein the static calibration area is provided with a first marker;
the camera collects images of the first marker in a static state of the driving equipment;
obtaining the image coordinate of a first characteristic point of the first marker according to the image of the first marker;
and obtaining static external parameters of the camera according to the image coordinates of the first characteristic point, the internal reference data of the camera and the coordinates of the first characteristic point in the navigation environment coordinate system, wherein the static external parameters comprise a static conversion relation between the navigation environment coordinate system and the camera coordinate system.
5. The calibration method according to claim 4, wherein the step of obtaining the image coordinates of the first feature point of the first marker from the image of the first marker comprises:
converting the color of the image of the first marker to an HSV color space;
filtering the converted image in an HSV color space;
inputting the filtered image into a recognizer of a deep learning model;
and obtaining the image coordinates of the first characteristic point according to the output result of the recognizer.
6. The calibration method according to claim 5, wherein the first marker comprises at least 3L-shaped painted markers.
7. The calibration method according to claim 4, wherein the dynamic external reference calibration comprises the steps of:
controlling the driving equipment to run to a dynamic calibration area, wherein the dynamic calibration area is provided with a second marker;
the camera acquires an image of a second marker in a driving state of the driving equipment;
and obtaining dynamic external parameters of the camera according to the image of the second marker and the static external parameters, wherein the dynamic external parameters comprise a dynamic conversion relation between the navigation environment coordinate system and the camera coordinate system.
8. The calibration method according to claim 7, wherein the second marker includes two parallel dynamic calibration lane lines respectively disposed on the left and right sides of the driving device, and the step of obtaining the dynamic external parameter of the camera according to the image of the second marker and the static external parameter includes:
obtaining vanishing point information of the dynamic calibration lane line according to the image of the second marker;
and obtaining dynamic external parameters according to the static external parameters and the vanishing point information.
9. The calibration method according to claim 8, wherein the first calibration information and the second calibration information include dynamic external parameters of the driving device under corresponding load conditions, and the step of obtaining the adaptive external parameters of the camera according to the first calibration information and the second calibration information includes:
obtaining a vanishing point change model according to dynamic external parameters of the driving equipment in different load states;
and fitting according to the vanishing point change model to obtain the self-adaptive external parameters of the camera.
10. The calibration method according to claim 8, further comprising the steps of:
obtaining vanishing point deviation data according to vanishing point information of the driving equipment in different load states;
and verifying the accuracy of the dynamic external parameter according to the vanishing point deviation data.
11. The calibration method according to claim 8, wherein the dynamic calibration lane line is provided with auxiliary short lines at preset intervals.
12. The calibration method according to any one of claims 1 to 11, wherein the driving device is an automatic driving device, and the cameras are mounted at the front end and the rear end of the automatic driving device.
13. A calibration system suitable for a camera of a driving device is characterized by comprising:
the static calibration area is provided with a first marker and is used for carrying out static external reference calibration on the camera;
the dynamic calibration area is provided with a second marker and is used for carrying out dynamic external reference calibration on the camera;
the calibration system calibrates the camera using the calibration method as claimed in any one of claims 7 to 11.
14. A computing device, comprising:
a processor adapted to implement various instructions;
a memory adapted to store a plurality of instructions adapted to be loaded by the processor and to perform the calibration method of any one of claims 1-12.
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