Multi-camera system calibration method, device, system, electronic device and storage medium

Abstract

The present disclosure provides a multi-camera system calibration method, device, system, electronic device and storage medium. The present disclosure first obtains multiple images of a target object simultaneously photographed by at least some cameras in the multi-camera system; then, based on the multiple images, a point cloud model of the target object is constructed; finally, based on difference information between the point cloud model and the target object, camera parameters of at least one camera in the multi-camera system are adjusted.

Description

Technical Field

[0001] The present disclosure relates to the field of image processing technology, and in particular to a multi-camera system calibration method, device, system, electronic device and storage medium. Background Art

[0002] Multiple cameras shoot objects from multiple angles, and the fields of view can be superimposed, and then through the construction of 3D models, the data obtained from the detection can be seamlessly integrated. Synchronous cameras can even shoot flexible objects (such as human bodies and animals), thus recording every moment of the object.

[0003] Tolerances in the design and manufacture of multi-angle camera systems may result in cameras not being set in the correct position or at the correct angle, for example, the cameras may be misaligned relative to each other in the horizontal or vertical direction. These defects may cause serious problems in the images generated by the multi-angle camera system, such as large color differences between different parts, severe distortion or double vision, which requires a lot of manual repair later or may not be repairable, seriously reducing the user experience. Summary of the invention

[0004] The embodiments of the present disclosure at least provide a multi-camera system calibration method, device, system, electronic device, and storage medium.

[0005] In a first aspect, an embodiment of the present disclosure provides a multi-camera system calibration method, comprising:

[0006] Acquire multiple images of a target object obtained by at least some cameras simultaneously photographing the target object in a multi-camera system;

[0007] Based on the multiple images, construct a point cloud model of the target object;

[0008] Based on the difference information between the point cloud model and the target object, camera parameters of at least one camera in the multi-camera system are adjusted.

[0009] In this regard, by adjusting the camera parameters by shooting the target object with multiple cameras at the same time, multiple pictures shot at multiple angles can be used to adjust the parameters of multiple cameras at the same time, which not only improves the efficiency of camera parameter adjustment, but also enables accurate parameter adjustment of cameras in a multi-camera system. The accuracy of parameters such as the position and angle of the camera after parameter adjustment is improved, which is conducive to improving the accuracy of 3D modeling using images taken by each camera in the multi-camera system, reducing the workload of post-repair of 3D modeling, and improving user experience.

[0010] In some possible implementations, the difference information includes size difference sub-information between the point cloud model and the target object;

[0011] Before adjusting the camera parameters of at least one camera in the multi-camera system based on the difference information between the point cloud model and the target object, the method further includes the step of determining the size difference sub-information:

[0012] Acquire standard size information of the target object and model size information of the point cloud model;

[0013] Determine difference information between the standard size information and the model size information to obtain the size difference sub-information;

[0014] The adjusting camera parameters of at least one camera in the multi-camera system based on the difference information between the point cloud model and the target object includes:

[0015] Based on the size difference sub-information between the point cloud model and the target object, camera parameters of at least one camera in the multi-camera system are adjusted.

[0016] In this embodiment, the size difference information between the point cloud model and the real target object can be accurately determined through the standard size information of the target object and the model size information of the point cloud model, that is, the size difference sub-information. The size difference sub-information can reflect the deviation of at least some cameras in the multi-camera system in terms of shooting position and shooting angle. Therefore, the camera parameters of the cameras in the multi-camera system can be adjusted using the size difference sub-information to effectively improve the adjustment accuracy.

[0017] In some possible implementations, adjusting camera parameters of at least one camera in the multi-camera system based on the size difference sub-information between the point cloud model and the target object includes:

[0018] Get the size difference threshold;

[0019] Determining a first target camera in the multi-camera system that needs to have its parameters adjusted based on the size difference sub-information between the point cloud model and the target object, and the size difference threshold;

[0020] Based on the size difference sub-information, a first preset parameter of the first target camera is adjusted.

[0021] This implementation method, using the preset size threshold, can more accurately determine whether the constructed point cloud model has obvious inaccuracies in size, that is, it can more accurately determine whether the cameras in the multi-camera system need to adjust the corresponding parameters, and can more accurately screen out the cameras that need to adjust the parameters, that is, the first target camera. The subsequent parameter adjustment of these cameras based on the size difference sub-information can not only improve the adjustment efficiency, but also effectively avoid the parameter adjustment of cameras that do not need parameter adjustment, thereby helping to improve the accuracy of parameter adjustment.

[0022] In some possible implementations, the target object includes at least one sub-block; the standard size information includes standard size sub-information corresponding to each sub-block; the model size information includes model size sub-information corresponding to each sub-block; the size difference sub-information includes first difference sub-information corresponding to each sub-block; wherein the first difference sub-information is used to characterize the difference information between the standard size sub-information and the model size sub-information of the corresponding sub-block.

[0023] In this implementation, the target object including at least one sub-block has multiple faces, each face or each block has size information, and the camera parameters are adjusted using the multiple size information, which is beneficial to improving the accuracy of parameter adjustment.

[0024] In some possible implementations, determining a first target camera in the multi-camera system that needs to have its parameters adjusted based on the size difference sub-information between the point cloud model and the target object and the size difference threshold includes:

[0025] Taking a sub-block whose difference value corresponding to the first difference sub-information is greater than the size difference threshold as a first target sub-block;

[0026] Determine a camera corresponding to the first target sub-block, and use the determined camera as a first target camera corresponding to the first target sub-block;

[0027] The adjusting the first preset parameter of the first target camera based on the size difference sub-information includes:

[0028] Based on the first difference sub-information corresponding to the first target sub-block, a first preset parameter of a first target camera corresponding to the first target sub-block is adjusted.

[0029] In this implementation mode, the size difference threshold is used to more accurately screen out sub-blocks with larger size deviations, namely, the first target sub-blocks mentioned above. Then, the first difference sub-information corresponding to the screened out first target sub-block is used to adjust the parameters of the camera corresponding to the first target sub-block, which can not only improve the adjustment efficiency, but also effectively avoid adjusting the parameters of irrelevant cameras, thereby facilitating improving the accuracy of the parameter adjustment.

[0030] In some possible implementations, adjusting camera parameters of at least one camera in the multi-camera system based on difference information between the point cloud model and the target object further includes:

[0031] After adjusting the first preset parameter of the first target camera based on the size difference sub-information, reacquiring a plurality of new images of the target object obtained by simultaneously photographing at least some of the cameras in the multi-camera system;

[0032] Reconstructing a new point cloud model of the target object based on the multiple new images, and determining new difference information between the new point cloud model and the target object;

[0033] When it is determined based on the size difference threshold that new size difference sub-information in the new difference information does not meet a first preset condition, camera parameters of at least one camera in the multi-camera system are adjusted based on the new size difference sub-information.

[0034] In this implementation, it is likely that the most accurate camera parameters cannot be obtained through a single parameter adjustment. Therefore, after the adjustment, through the steps of point cloud model reconstruction and re-determining new difference information, it is possible to more accurately determine whether the cameras in the multi-camera system are adjusted to obtain the most accurate camera parameters. When the cameras in the multi-camera system are not adjusted to obtain the most accurate camera parameters, the camera parameters are adjusted again, which can effectively improve the adjustment accuracy.

[0035] In some possible implementations, the difference information includes color difference sub-information between the point cloud model and the target object;

[0036] The adjusting camera parameters of at least one camera in the multi-camera system based on the difference information between the point cloud model and the target object further includes:

[0037] When it is determined based on the size difference threshold that the new size difference sub-information in the new difference information satisfies a first preset condition, obtaining a color difference threshold;

[0038] Determining a second target camera in the multi-camera system that needs to have its parameters adjusted based on the color difference sub-information between the point cloud model and the target object, and the color difference threshold;

[0039] Based on the color difference sub-information, a second preset parameter of the second target camera is adjusted.

[0040] In this implementation, after the adjustment of the first preset parameters such as the shooting position and the shooting angle is completed, the second preset parameters such as the camera aperture are further adjusted using the color difference sub-information and the color difference threshold, which can improve the integrity and accuracy of the camera parameter adjustment. Furthermore, using the color preset threshold, it is possible to more accurately determine whether the constructed point cloud model has obvious inaccuracies in color, that is, it is possible to more accurately determine whether the cameras in the multi-camera system need to adjust the corresponding parameters, and it is possible to more accurately screen out the cameras that need to adjust the parameters, that is, the second target cameras. The subsequent adjustment of the parameters of these cameras based on the color difference sub-information can not only improve the adjustment efficiency, but also effectively avoid adjusting the parameters of cameras that do not need to be adjusted, thereby helping to improve the accuracy of the parameter adjustment.

[0041] In some possible implementations, the difference information includes color difference sub-information between the point cloud model and the target object;

[0042] The adjusting camera parameters of at least one camera in the multi-camera system based on the difference information between the point cloud model and the target object includes:

[0043] Get the color difference threshold;

[0044] Determining a second target camera in the multi-camera system that needs to have its parameters adjusted based on the color difference sub-information between the point cloud model and the target object, and the color difference threshold;

[0045] Based on the color difference sub-information, a second preset parameter of the second target camera is adjusted.

[0046] This implementation method uses the preset color threshold to more accurately determine whether the constructed point cloud model has obvious inaccuracies in color, that is, it can more accurately determine whether the cameras in the multi-camera system need to adjust the corresponding parameters, and can more accurately screen out the cameras that need to adjust the parameters, that is, the second target camera. The subsequent parameter adjustment of these cameras based on the color difference sub-information can not only improve the adjustment efficiency, but also effectively avoid the parameter adjustment of cameras that do not need parameter adjustment, thereby helping to improve the accuracy of parameter adjustment.

[0047] In some possible embodiments, the target object includes at least one sub-block; the color difference sub-information includes second difference sub-information corresponding to each sub-block; wherein the second difference sub-information is used to characterize the difference information between the color information of the corresponding sub-block in the point cloud model and the actual color information.

[0048] In this implementation manner, the target object of at least one sub-block has multiple faces, each face or each block has color information, and the camera parameters are adjusted using multiple color information, which is beneficial to improving the accuracy of parameter adjustment.

[0049] In some possible implementations, determining a second target camera in the multi-camera system that needs to have its parameters adjusted based on the color difference sub-information between the point cloud model and the target object and the color difference threshold includes:

[0050] Taking the sub-block whose difference value corresponding to the second difference sub-information is greater than the color difference threshold as the second target sub-block;

[0051] Determine a camera corresponding to the second target sub-block, and use the determined camera as a second target camera corresponding to the second target sub-block;

[0052] The adjusting the second preset parameter of the second target camera based on the color difference sub-information includes:

[0053] Based on the second difference sub-information corresponding to the second target sub-block, a second preset parameter of a second target camera corresponding to the second target sub-block is adjusted.

[0054] In this implementation manner, the color difference threshold can be used to relatively accurately screen out sub-blocks with large color deviations, namely, the second target sub-blocks mentioned above; then, the second difference sub-information corresponding to the screened second target sub-block is used to adjust the parameters of the camera corresponding to the second target sub-block, which can not only improve the adjustment efficiency, but also effectively avoid adjusting the parameters of irrelevant cameras, thereby facilitating improving the accuracy of the parameter adjustment.

[0055] In some possible implementations, adjusting camera parameters of at least one camera in the multi-camera system based on difference information between the point cloud model and the target object further includes:

[0056] After adjusting the second preset parameter of the second target camera based on the color difference sub-information, reacquiring a plurality of new images obtained by simultaneously photographing the target object by at least some cameras in the multi-camera system;

[0057] Reconstructing a new point cloud model of the target object based on the multiple new images, and determining new difference information between the new point cloud model and the target object;

[0058] When it is determined based on the color difference threshold that the new color difference sub-information in the new difference information does not satisfy the second preset condition, the second preset parameter of the second target camera is adjusted based on the new color difference sub-information.

[0059] In this implementation, it is likely that the most accurate camera parameters cannot be obtained through a single parameter adjustment. Therefore, after the adjustment, through the steps of point cloud model reconstruction and re-determining new difference information, it is possible to more accurately determine whether the cameras in the multi-camera system are adjusted to obtain the most accurate camera parameters. When the cameras in the multi-camera system are not adjusted to obtain the most accurate camera parameters, the camera parameters are adjusted again, which can effectively improve the adjustment accuracy.

[0060] In some possible implementations, different cameras in the multi-camera system have different shooting angles for the target object, and a target shooting angle obtained by superimposing the shooting angles of each camera is an omnidirectional shooting angle corresponding to the target object.

[0061] This implementation can ensure that the multi-camera system can capture the entire target object.

[0062] In some possible implementations, the distance between each camera and the target object satisfies a preset condition; wherein the preset condition includes that the shooting field of view of each camera for the target object forms a sphere or annulus, and the target object is located at a preset position within the sphere or annulus, so that the similarity of the light reflected by the target object to each camera is higher than a preset similarity.

[0063] This implementation can ensure that the light used by each camera in the multi-camera system to capture the target object is relatively consistent, which is beneficial to improving the accuracy of calibration.

[0064] In a second aspect, the present disclosure also provides a multi-camera system calibration device, including:

[0065] An image acquisition module, used to acquire multiple images of a target object obtained by at least some cameras simultaneously photographing the target object in a multi-camera system;

[0066] A modeling module, used for constructing a point cloud model of the target object based on the multiple images;

[0067] An adjustment module is used to adjust camera parameters of at least one camera in the multi-camera system based on difference information between the point cloud model and the target object.

[0068] In a third aspect, an embodiment of the present disclosure further provides a multi-camera system calibration system, characterized in that it includes multiple cameras, a camera parameter adjustment component, and a target object; the target object is set within a target shooting field of view formed by the multiple cameras;

[0069] At least some of the multiple cameras are used to simultaneously capture images of the target object, and send the captured images to the camera parameter adjustment component;

[0070] The camera parameter adjustment component is used to adjust the parameters of at least one camera among the multiple cameras according to the multi-camera system calibration method.

[0071] In a fourth aspect, an embodiment of the present disclosure further provides an electronic device, comprising: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate via the bus, and when the machine-readable instructions are executed by the processor, the steps of the above-mentioned first aspect, or any possible implementation of the first aspect are performed.

[0072] In a fifth aspect, an embodiment of the present disclosure further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned first aspect or any possible implementation of the first aspect are executed.

[0073] For a description of the effects of the above-mentioned multi-camera system calibration device, system, electronic device, and computer-readable storage medium, please refer to the description of the above-mentioned multi-camera system calibration method, which will not be repeated here.

[0074] In order to make the above-mentioned objectives, features and advantages of the present disclosure more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following is a brief introduction to the drawings required for use in the embodiments. The drawings herein are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments consistent with the present disclosure and are used together with the specification to illustrate the technical solutions of the present disclosure. It should be understood that the following drawings only illustrate certain embodiments of the present disclosure and should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can also be obtained based on these drawings without creative work.

[0076] Figure 1 A schematic diagram of a multi-camera system provided by an embodiment of the present disclosure is shown;

[0077] Figure 2 A flow chart of a multi-camera system calibration method provided by an embodiment of the present disclosure is shown;

[0078] Figure 3 A schematic diagram showing a target object photographed by multiple cameras provided in an embodiment of the present disclosure is shown;

[0079] Figure 4 A flowchart of another multi-camera system calibration method provided by an embodiment of the present disclosure is shown;

[0080] Figure 5 A schematic diagram of the architecture of a multi-camera system calibration device provided by an embodiment of the present disclosure is shown;

[0081] Figure 6 A schematic diagram of the architecture of a multi-camera system calibration system provided by an embodiment of the present disclosure is shown;

[0082] Figure 7 A schematic diagram of an electronic device provided by an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0083] In order to make the purpose, technical scheme and advantages of the embodiments of the present disclosure clearer, the technical scheme in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all of the embodiments. The components of the embodiments of the present disclosure generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present disclosure provided in the drawings is not intended to limit the scope of the present disclosure for protection, but merely represents the selected embodiments of the present disclosure. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present disclosure.

[0084] like Figure 1As shown in FIG. 1 , a multi-camera system uses multiple cameras to shoot an object from multiple angles, and then uses the multiple pictures to build a color 3D model. The application of this technology is becoming more and more common. Multiple cameras shoot objects from multiple angles, the fields of view can be superimposed, and the data can be seamlessly integrated. Synchronous combined cameras can even shoot flexible objects (such as human bodies and animals), thereby recording every moment of the object. There will be slight differences in camera parameters between multiple cameras. Tolerances in the design and manufacturing of multi-camera systems may cause the cameras to not be set in the correct position or at the correct angle. For example, the cameras may be misaligned relative to each other in the horizontal or vertical direction. These defects may cause serious problems in the images generated by the multi-angle camera system, such as large color differences in different parts, severe distortion, or double vision, which requires a lot of manual repair in the later stage or even cannot be repaired, seriously reducing the user experience.

[0085] In addition, the multiple cameras of a multi-camera system may not be positioned or oriented as intended by the design, in which case the actual position of the camera and its relative rotation with respect to the design are unknown. This problem can lead to visual artifacts when combining images captured by multiple cameras. For example, color spots may appear when generating overlapping images between two cameras.

[0086] In response to the above technical problems, the present disclosure provides a multi-camera system calibration method, device, system, electronic device and storage medium. The present disclosure adjusts camera parameters by shooting target objects with multiple cameras at the same time, and can use multiple pictures shot at multiple angles to adjust the parameters of multiple cameras at the same time, which can not only improve the efficiency of camera parameter adjustment, but also accurately adjust the parameters of cameras in the multi-camera system. The accuracy of parameters such as the position and angle of the camera after parameter adjustment is improved, which is conducive to improving the accuracy of 3D modeling using images shot by each camera in the multi-camera system, reducing the workload of post-repair of 3D modeling, and improving user experience.

[0087] The multi-camera system calibration method provided by the embodiment of the present disclosure is described below by taking the execution subject as a device or system with computing capabilities as an example.

[0088] like Figure 2 As shown, the multi-camera system calibration method provided by the present disclosure may include the following steps:

[0089] S210: Acquire multiple images of a target object obtained by simultaneously photographing at least some cameras in a multi-camera system.

[0090] The above-mentioned multi-camera system includes multiple cameras with different shooting angles, such as Figure 3As shown, four cameras with different shooting angles may be included: camera 1, camera 2, camera 3 and camera 4. The four cameras shoot the target object from different angles, so that images of different angles of the target object can be obtained. The fusion of the four images can obtain an all-round image of the target object. That is, different cameras in the multi-camera system have different shooting angles for the target object, and the target shooting angle obtained by superimposing the shooting angles of each camera is the all-round shooting angle corresponding to the target object. This can ensure that the multi-camera system can capture the complete target object, which is conducive to improving the accuracy of camera calibration.

[0091] The target object may be an object with multiple faces, and different faces may have different information such as positions and colors. Adjusting the camera parameters using multiple information of the target object with multiple faces can improve the accuracy of the adjustment.

[0092] Exemplarily, the target object may include at least one sub-block, such as Figure 3 As shown, the target object may be a Rubik's Cube 301 having a plurality of movably connected sub-blocks. The camera parameters may be adjusted by using the positions, colors and other information of the plurality of sub-blocks in the Rubik's Cube. This allows the camera parameters to be adjusted using more information, thereby effectively improving the accuracy of the adjustment.

[0093] The above images may be taken by multiple cameras at the same time, and the multiple images can reflect the parameter information of the corresponding multiple cameras at the time of shooting, such as shooting position, shooting angle, shooting aperture, etc. The multiple images taken at the same time can be used to adjust the parameters of the multiple cameras shooting the images at the same time.

[0094] Exemplarily, the distance between each camera and the target object satisfies a preset condition; wherein the preset condition includes that the shooting field of view of each camera for the target object forms a sphere or annulus, and the target object is located at a preset position within the sphere or annulus, so that the similarity of the light reflected by the target object to each camera is higher than the preset similarity. For example, the target object is located at the center of the sphere or annulus, so that the light used by each camera to shoot the image of the target object is relatively consistent, and the target object is relatively consistent in color, structure, texture, shape, etc., which is conducive to improving the accuracy of calibration.

[0095] S220: constructing a point cloud model of the target object based on the multiple images.

[0096] Here, multiple images can be processed by photogrammetry tool software to obtain a colored point cloud three-dimensional model, that is, the above-mentioned point cloud model.

[0097] S230: Adjust camera parameters of at least one camera in the multi-camera system based on difference information between the point cloud model and the target object.

[0098] The above-mentioned difference information may include the difference between the point cloud model and the real target object in size and / or color. Such difference information can reflect the deviation of the camera used to capture the image in shooting position, shooting angle, and shooting aperture. Therefore, by adjusting the camera parameters of the cameras in the multi-camera system through the above-mentioned difference information, the adjustment accuracy can be effectively improved.

[0099] In some embodiments, the difference information may include size difference sub-information between the point cloud model and the target object. Before adjusting the camera parameters of at least one camera in the multi-camera system based on the difference information between the point cloud model and the target object, the size difference sub-information needs to be determined:

[0100] First, the standard size information of the target object and the model size information of the point cloud model are obtained; then, the difference information between the standard size information and the model size information is determined to obtain the size difference sub-information.

[0101] After determining the size difference sub-information, the camera parameters of at least one camera in the multi-camera system are adjusted based on the difference information between the point cloud model and the target object. Specifically, the camera parameters of at least one camera in the multi-camera system are adjusted based on the size difference sub-information between the point cloud model and the target object.

[0102] The size difference information between the point cloud model and the real target object can be accurately determined by using the standard size information of the target object and the model size information of the point cloud model, that is, the size difference sub-information. The size difference sub-information can reflect the deviation of at least some cameras in the multi-camera system in terms of shooting position and shooting angle. Therefore, the camera parameters of the cameras in the multi-camera system can be adjusted by using the size difference sub-information to effectively improve the adjustment accuracy.

[0103] Exemplarily, after determining the size difference sub-information, the following steps may be used to implement the above determination to adjust camera parameters of at least one camera in the multi-camera system based on the size difference sub-information between the point cloud model and the target object:

[0104] First, a size difference threshold is obtained; then, based on the size difference sub-information between the point cloud model and the target object, and the size difference threshold, a first target camera in the multi-camera system that needs to have its parameters adjusted is determined; finally, based on the size difference sub-information, a first preset parameter of the first target camera is adjusted.

[0105] The size difference threshold may be set according to specific needs and scenarios, for example, set to 0.01, which is not limited in the present disclosure.

[0106] By using the preset size threshold, it is possible to more accurately determine whether the constructed point cloud model has obvious inaccuracies in size, that is, it is possible to more accurately determine whether the cameras in the multi-camera system need to adjust the corresponding parameters, and it is possible to more accurately screen out the cameras that need to be adjusted, that is, the first target cameras. Subsequently, the parameters of these cameras are adjusted according to the size difference sub-information, which can not only improve the adjustment efficiency, but also effectively avoid adjusting the parameters of cameras that do not need to be adjusted, thereby helping to improve the accuracy of parameter adjustment.

[0107] Exemplarily, the target object includes at least one sub-block; the standard size information includes standard size sub-information corresponding to each sub-block, for example, the standard size information includes a standard length value, a standard width value, and a standard height value of each sub-block. The model size information includes model size sub-information corresponding to each sub-block, for example, the model size information includes a model length value, a model width value, and a model height value of each sub-block. The size difference sub-information includes first difference sub-information corresponding to each sub-block, wherein the first difference sub-information is used to characterize the difference information between the standard size sub-information and the model size sub-information of the corresponding sub-block.

[0108] Exemplarily, the first difference sub-information corresponding to a sub-block may be determined using the following formula:

[0109]

[0110] In the formula, D1 represents the above-mentioned first difference sub-information, x1 represents the standard value of length, y1 represents the standard value of width, z1 represents the standard value of height, x2 represents the model length value, y2 represents the model width value, and z2 represents the model height value.

[0111] The target object including at least one sub-block has multiple faces, each face or each block has size information, and adjusting the camera parameters using the multiple size information is beneficial to improving the accuracy of parameter adjustment.

[0112] After determining the first difference sub-information of each sub-block object, the following steps may be used to determine the first target camera in the multi-camera system that needs to have its parameters adjusted:

[0113] First, a sub-block corresponding to the first difference sub-information and having a difference value greater than the size difference threshold is taken as a first target sub-block; then, a camera corresponding to the first target sub-block is determined, and the determined camera is taken as a first target camera corresponding to the first target sub-block.

[0114] After determining the first target camera corresponding to a first target sub-block, the following steps may be used to adjust the parameters of the first target camera corresponding to the first target sub-block:

[0115] Based on the first difference sub-information corresponding to the first target sub-block, the first preset parameter of the first target camera corresponding to the first target sub-block is adjusted. The size difference threshold can be used to more accurately screen out sub-blocks with large size deviations, that is, the first target sub-blocks mentioned above; then, the first difference sub-information corresponding to the screened first target sub-block is used to adjust the parameters of the camera corresponding to the first target sub-block, which can not only improve the adjustment efficiency, but also effectively avoid adjusting the parameters of irrelevant cameras, thereby facilitating the improvement of the accuracy of parameter adjustment.

[0116] The first preset parameter may be a shooting position, a shooting angle, etc. of the corresponding camera.

[0117] When adjusting the first preset parameters of the first target camera corresponding to the first target sub-block based on the first difference sub-information corresponding to the first target sub-block, the first preset parameters of the corresponding first target camera can be adjusted manually according to the first difference sub-information. Of course, it can also be implemented by the following steps: based on the first difference sub-information corresponding to the first target sub-block, determine the first target parameter information such as the target shooting position and the target shooting angle of the corresponding first target camera; then, according to the current shooting position, shooting angle and other parameter information of the current first target camera and the above-mentioned first target parameter information, determine the first parameter adjustment information such as the position adjustment information and the angle adjustment information; finally, adjust the first preset parameters such as the shooting position and shooting angle of the first target camera according to the above-mentioned first parameter adjustment information.

[0118] It is very likely that the most accurate camera parameters cannot be obtained through a single parameter adjustment. Therefore, after the adjustment, the image can be recaptured, and the point cloud model can be reconstructed to re-determine the new difference information and other steps to determine whether the cameras in the multi-camera system have been adjusted to obtain the most accurate camera parameters. If the cameras in the multi-camera system have not been adjusted to obtain the most accurate camera parameters, the camera parameters can be adjusted again to improve the adjustment accuracy. Exemplarily, the above-mentioned first preset parameters of the camera can be adjusted again or multiple times using the following steps:

[0119] First, after adjusting the first preset parameters of the first target camera based on the size difference sub-information, a plurality of new images obtained by simultaneously photographing the target object by at least some cameras in the multi-camera system are reacquired; then, based on the plurality of new images, a new point cloud model of the target object is reconstructed, and new difference information between the new point cloud model and the target object is determined; finally, when it is determined based on the size difference threshold that new size difference sub-information in the new difference information does not meet the first preset condition, camera parameters of at least one camera in the multi-camera system are adjusted based on the new size difference sub-information.

[0120] Specifically, the new size difference sub-information in the new difference information does not satisfy the first preset condition, which may be that there is at least one sub-block corresponding to the new first difference sub-information with a difference value greater than the size difference threshold. Specifically, the new size difference sub-information in the new difference information satisfies the first preset condition, which may be that the difference values ​​of the new first difference sub-information corresponding to all sub-blocks are less than the size difference threshold.

[0121] The implementation steps of adjusting the camera parameters of at least one camera in the multi-camera system based on the new size difference sub-information are the same as the steps of adjusting the camera parameters of at least one camera in the multi-camera system based on the size difference sub-information in the above embodiment, and are not repeated here.

[0122] When the new size difference sub-information in the new difference information satisfies the first preset condition, the second preset parameters such as the camera's shooting aperture can be further adjusted. Of course, the second preset parameters such as the camera's shooting aperture can also be directly adjusted. In this case, the first preset parameters and the second preset parameters are two independent and unrelated steps. The adjustment of the second preset parameters is described below.

[0123] Exemplarily, the difference information includes color difference sub-information between the point cloud model and the target object. The target object includes at least one sub-block; the color difference sub-information includes second difference sub-information corresponding to each sub-block; wherein the second difference sub-information is used to represent the difference between the color information of the corresponding sub-block in the point cloud model and the real color information.

[0124] The target object of at least one sub-block has multiple faces, each face or each block has color information, and adjusting the camera parameters using multiple color information is beneficial to improving the accuracy of parameter adjustment.

[0125] After determining the color difference sub-information between the point cloud model and the target object, the color difference sub-information is adjusted for at least one camera in the multi-camera system based on the color difference information between the point cloud model and the target object. Specifically, the color difference sub-information can be implemented by the following steps:

[0126] First, a color difference threshold is obtained; then, based on the color difference sub-information between the point cloud model and the target object, and the color difference threshold, a second target camera in the multi-camera system that needs to have its parameters adjusted is determined; finally, based on the color difference sub-information, a second preset parameter of the second target camera is adjusted.

[0127] The color difference threshold may be set according to specific needs and scenarios, for example, set to 0.01, which is not limited in the present disclosure.

[0128] By using the preset color threshold, it is possible to more accurately determine whether the constructed point cloud model has obvious inaccuracies in color, that is, it is possible to more accurately determine whether the cameras in the multi-camera system need to adjust the corresponding parameters, and it is possible to more accurately screen out the cameras that need to be adjusted, that is, the second target camera. Subsequently, the parameters of these cameras are adjusted according to the color difference sub-information, which can not only improve the adjustment efficiency, but also effectively avoid adjusting the parameters of cameras that do not need to be adjusted, thereby helping to improve the accuracy of parameter adjustment.

[0129] Exemplarily, the target object includes at least one sub-block; the color difference sub-information includes second difference sub-information corresponding to each sub-block; wherein the second difference sub-information is used to represent the difference information between the color information of the corresponding sub-block in the point cloud model and the real color information. The color information of a sub-block in the point cloud model includes the model RGB value of the sub-block, and the real color information of a sub-block includes the standard RGB value of the sub-block.

[0130] Exemplarily, the second difference sub-information corresponding to a sub-block may be determined using the following formula:

[0131]

[0132] In the formula, D2 represents the above-mentioned second difference sub-information, R1 represents the standard R value in the standard RGB value, G1 represents the standard G value in the standard RGB value, B1 represents the standard B value in the standard RGB value, R2 represents the model R value in the model RGB value, G2 represents the model G value in the model RGB value, and B2 represents the model B value in the model RGB value.

[0133] After determining the second difference sub-information of each sub-block object, the following steps may be used to determine the second target camera in the multi-camera system that needs to have its parameters adjusted:

[0134] First, a sub-block corresponding to the second difference sub-information and having a difference value greater than the color difference threshold is used as a second target sub-block; then, a camera corresponding to the second target sub-block is determined, and the determined camera is used as a second target camera corresponding to the second target sub-block.

[0135] After determining the second target camera corresponding to a second target sub-block, the following steps may be used to adjust the parameters of the second target camera corresponding to the second target sub-block:

[0136] Based on the second difference sub-information corresponding to the second target sub-block, the second preset parameter of the second target camera corresponding to the second target sub-block is adjusted. The color difference threshold can be used to more accurately screen out the sub-block with a large color deviation, that is, the second target sub-block mentioned above; then, the second difference sub-information corresponding to the screened second target sub-block is used to adjust the parameters of the camera corresponding to the second target sub-block, which can not only improve the adjustment efficiency, but also effectively avoid adjusting the parameters of irrelevant cameras, thereby facilitating the improvement of the accuracy of the parameter adjustment.

[0137] The second preset parameter may correspond to the shooting aperture, shutter speed, sensitivity, etc. of the camera.

[0138] When adjusting the second preset parameters of the second target camera corresponding to the second target sub-block based on the second difference sub-information corresponding to the second target sub-block, the second preset parameters of the corresponding second target camera can be adjusted manually according to the second difference sub-information. Of course, it can also be implemented by the following steps: based on the second difference sub-information corresponding to the second target sub-block, determine the second target parameter information such as the target shooting aperture and the target sensitivity of the corresponding second target camera; then, according to the current shooting aperture, sensitivity and other parameter information of the current second target camera and the above-mentioned second target parameter information, determine the second parameter adjustment information such as the aperture adjustment information and the sensitivity adjustment information; finally, adjust the second preset parameters such as the shooting aperture and sensitivity of the second target camera according to the above-mentioned second parameter adjustment information.

[0139] It is very likely that the most accurate camera parameters cannot be obtained through a single parameter adjustment. Therefore, after the adjustment, the point cloud model is reconstructed, and new difference information is re-determined. It can be more accurately determined whether the cameras in the multi-camera system have been adjusted to obtain the most accurate camera parameters. When the cameras in the multi-camera system have not been adjusted to obtain the most accurate camera parameters, the camera parameters are adjusted again, which can effectively improve the adjustment accuracy. Exemplarily, the second preset parameters of the camera can be adjusted again or multiple times using the following steps:

[0140] First, after adjusting the second preset parameters of the second target camera based on the color difference sub-information, a plurality of new images obtained by simultaneously photographing the target object by at least some cameras in the multi-camera system are reacquired; then, based on the plurality of new images, a new point cloud model of the target object is reconstructed, and new difference information between the new point cloud model and the target object is determined; finally, when it is determined based on the color difference threshold that new color difference sub-information in the new difference information does not meet the second preset condition, the second preset parameters of the second target camera are adjusted based on the new color difference sub-information.

[0141] Specifically, the new color difference sub-information in the new difference information does not satisfy the second preset condition, which may be that there is at least one sub-block corresponding to the new second difference sub-information with a difference value greater than the color difference threshold. Specifically, the new color difference sub-information in the new difference information satisfies the second preset condition, which may be that the difference values ​​of the new second difference sub-information corresponding to all sub-blocks are less than the color difference threshold.

[0142] The implementation steps of adjusting the second preset parameters of the second target camera based on the new color difference sub-information are the same as the steps of adjusting the second preset parameters of the second target camera based on the color difference sub-information in the above embodiment, and are not repeated here.

[0143] The above embodiment can perform one or more rounds of parameter adjustment. During one round of parameter adjustment, different images provided by multiple cameras can capture a target object located at the center of the multi-camera system, such as a set of images of a Rubik's Cube. Modeling is performed based on the captured images to obtain a point cloud model, and detailed information of the target object is generated at the same time, such as the position, size, shape, color, and texture of the Rubik's Cube. The camera parameters are then adjusted based on the detailed information of the target object obtained by modeling and the standard information of the target object. The Rubik's Cube can change its shape, so that multiple point cloud models can be generated for multiple verifications.

[0144] The method in the above embodiment can quickly obtain the error of each camera parameter and realize accurate adjustment of the camera parameters, which can generally be calibrated correctly within 10 minutes, thus avoiding the situation in the prior art where manual adjustment requires 2 to 20 hours of calibration time.

[0145] The multi-camera system calibration method in the present disclosure is described below through a specific embodiment. Figure 4 As shown:

[0146] Step 1: Place the system including the target object three-order Rubik's Cube, multiple cameras, and target parameter adjustment components at the shooting range test site. The shooting range test site layout is the same as the traditional multi-angle shooting camera system. The three-order Rubik's Cube is set at the center of the target shooting field of view formed by multiple cameras, and the multi-camera system surrounds the three-order Rubik's Cube in a spherical or cylindrical shape. All cameras are aimed at the Rubik's Cube to capture images. Multiple cameras are connected to the target parameter adjustment components, such as computers, through network cables and routers. Group control system software, photogrammetry tool software, and calibration system software are installed on the computer. Among them, the calibration system software stores the standard length value x1, width standard value y1, height standard value z1 of each sub-block of the Rubik's Cube, as well as the standard R value R1, standard G value G1, and standard B value B1 in the standard RGB value of each sub-block.

[0147] Step 2: Using the group control system software on a computer, control at least some of the cameras in the multi-camera system to take photos simultaneously, thereby obtaining multiple original images.

[0148] Step 3: Transfer the original images taken by different cameras to the computer through the group control system software.

[0149] Step 4: Process multiple original images using photogrammetry tool software to obtain a colored three-dimensional point cloud model of the Rubik's Cube.

[0150] Step 5: The calibration system software calculates the model length value x2, model width value y2, and model height value z2 of each sub-block in the point cloud model, and combines them with the built-in x1, y1, and z1 of the calibration system software to obtain the first difference sub-information D1.

[0151] Determine that the sub-block corresponding to the difference value corresponding to the first difference sub-information is greater than the size difference threshold corresponds to a camera, namely, a first target camera. If it is determined that there is no first target camera, jump to step seven.

[0152] Step 6: Adjust the first preset parameters such as the shooting position and shooting direction of the first target camera. Return to step 1 after the adjustment is completed.

[0153] Step 7: The calibration system software calculates the model RGB value of each sub-block in the point cloud model: model R value R2 in the model RGB value, model G value G2 in the model RGB value, and model B value B2 in the model RGB value. Combined with the built-in R1, G1, and B1 of the calibration system, the second difference sub-information D2 is obtained;

[0154] It is determined that the sub-block corresponding to the difference value of the second difference sub-information is greater than the color difference threshold corresponds to the second target camera. If it is determined that there is no second target camera, the process jumps to step nine.

[0155] Step 8: Adjust the second preset parameters such as the shooting aperture and sensitivity of the second target camera.

[0156] Step nine: Continue calibration until the difference values ​​corresponding to the second difference sub-information of all sub-blocks are smaller than the color difference threshold.

[0157] Those skilled in the art will appreciate that, in the above method of specific implementation, the order in which the steps are written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of the steps should be determined by their functions and possible internal logic.

[0158] Based on the same inventive concept, the embodiment of the present disclosure also provides a multi-camera system calibration device corresponding to the multi-camera system calibration method. Since the principle of solving the problem by the device in the embodiment of the present disclosure is similar to the multi-camera system calibration method mentioned above in the embodiment of the present disclosure, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0159] Reference Figure 5 FIG. 1 is a schematic diagram of the architecture of a multi-camera system calibration device provided by an embodiment of the present disclosure, wherein the device comprises:

[0160] The image acquisition module 510 is used to acquire multiple images of a target object obtained by at least some cameras simultaneously photographing the target object in a multi-camera system.

[0161] The modeling module 520 is used to construct a point cloud model of the target object based on the multiple images.

[0162] The adjustment module 530 is used to adjust camera parameters of at least one camera in the multi-camera system based on the difference information between the point cloud model and the target object.

[0163] Based on the same inventive concept, the embodiment of the present disclosure also provides a multi-camera system calibration system corresponding to the multi-camera system calibration method. Since the principle of solving the problem by the system in the embodiment of the present disclosure is similar to the multi-camera system calibration method mentioned above in the embodiment of the present disclosure, the implementation of the system can refer to the implementation of the method, and the repeated parts will not be repeated.

[0164] Reference Figure 6 , which is a schematic diagram of the architecture of a multi-camera system calibration system provided in an embodiment of the present disclosure, wherein the system includes multiple cameras 610, a camera parameter adjustment component 620, and a target object 630.

[0165] The target object 630 is set within the target shooting field of view formed by the multiple cameras 610. At least some of the multiple cameras 610 are used to simultaneously shoot images of the target object 630, and send the captured images to the camera parameter adjustment component 620; the camera parameter adjustment component 620 is used for the multi-camera system calibration method in the above embodiment to adjust the parameters of at least one camera among the multiple cameras.

[0166] Based on the same technical concept, the embodiment of the present disclosure also provides an electronic device. Figure 7 As shown, it is a schematic diagram of the structure of the electronic device 700 provided in the embodiment of the present disclosure, including a processor 71, a memory 72, and a bus 73. Among them, the memory 72 is used to store execution instructions, including a memory 721 and an external memory 722; the memory 721 here is also called an internal memory, which is used to temporarily store the operation data in the processor 71, and the data exchanged with the external memory 722 such as a hard disk. The processor 71 exchanges data with the external memory 722 through the memory 721. When the electronic device 700 is running, the processor 71 communicates with the memory 72 through the bus 73, so that the processor 71 executes the following instructions:

[0167] Acquire multiple images of a target object simultaneously captured by at least some cameras in a multi-camera system; construct a point cloud model of the target object based on the multiple images; and adjust camera parameters of at least one camera in the multi-camera system based on difference information between the point cloud model and the target object.

[0168] The present disclosure also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the multi-camera system calibration method described in the above method embodiment are executed. The storage medium can be a volatile or non-volatile computer-readable storage medium.

[0169] The computer program product of the multi-camera system calibration method provided in the embodiment of the present disclosure includes a computer-readable storage medium storing a program code, and the instructions included in the program code can be used to execute the steps of the multi-camera system calibration method described in the above method embodiment. For details, please refer to the above method embodiment, which will not be repeated here. The computer program product can be implemented in hardware, software or a combination thereof. In an optional embodiment, the computer program product is specifically embodied as a computer storage medium. In another optional embodiment, the computer program product is specifically embodied as a software product, such as a software development kit (Software Development Kit, SDK) and the like.

[0170] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, the specific working process of the system and device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. In the several embodiments provided in the present disclosure, it should be understood that the disclosed system, device and method can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of the device or unit can be electrical, mechanical or other forms.

[0171] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0172] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0173] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present disclosure, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present disclosure. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0174] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present disclosure, which are used to illustrate the technical solutions of the present disclosure, rather than to limit them. The protection scope of the present disclosure is not limited thereto. Although the present disclosure is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed in the present disclosure, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure, and should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A multi-camera system calibration method, characterized in that: include: Acquire multiple images of a target object obtained by at least some cameras simultaneously photographing the target object in a multi-camera system; Based on the multiple images, construct a point cloud model of the target object; Based on the difference information between the point cloud model and the target object, adjusting the camera parameters of at least one camera in the multi-camera system; The difference information includes color difference sub-information between the point cloud model and the target object; The adjusting camera parameters of at least one camera in the multi-camera system based on the difference information between the point cloud model and the target object includes: Get the color difference threshold; Determining a second target camera in the multi-camera system that needs to have its parameters adjusted based on the color difference sub-information between the point cloud model and the target object, and the color difference threshold; Based on the color difference sub-information, a second preset parameter of the second target camera is adjusted.

2. The method according to claim 1, characterized in that The difference information includes size difference sub-information between the point cloud model and the target object; Before adjusting the camera parameters of at least one camera in the multi-camera system based on the difference information between the point cloud model and the target object, the method further includes the step of determining the size difference sub-information: Acquire standard size information of the target object and model size information of the point cloud model; Determine difference information between the standard size information and the model size information to obtain the size difference sub-information; The adjusting camera parameters of at least one camera in the multi-camera system based on the difference information between the point cloud model and the target object includes: Based on the size difference sub-information between the point cloud model and the target object, camera parameters of at least one camera in the multi-camera system are adjusted.

3. The method according to claim 2, characterized in that The adjusting camera parameters of at least one camera in the multi-camera system based on the size difference sub-information between the point cloud model and the target object comprises: Get the size difference threshold; Determining a first target camera in the multi-camera system that needs to have its parameters adjusted based on the size difference sub-information between the point cloud model and the target object, and the size difference threshold; Based on the size difference sub-information, a first preset parameter of the first target camera is adjusted.

4. The method according to claim 3, characterized in that The target object includes at least one sub-block; the standard size information includes standard size sub-information corresponding to each sub-block; the model size information includes model size sub-information corresponding to each sub-block; the size difference sub-information includes first difference sub-information corresponding to each sub-block; wherein the first difference sub-information is used to characterize the difference information between the standard size sub-information and the model size sub-information of the corresponding sub-block.

5. The method according to claim 4, characterized in that The determining, based on the size difference sub-information between the point cloud model and the target object and the size difference threshold, a first target camera in the multi-camera system that needs to have its parameters adjusted includes: Taking a sub-block whose difference value corresponding to the first difference sub-information is greater than the size difference threshold as a first target sub-block; Determine a camera corresponding to the first target sub-block, and use the determined camera as a first target camera corresponding to the first target sub-block; The adjusting the first preset parameter of the first target camera based on the size difference sub-information includes: Based on the first difference sub-information corresponding to the first target sub-block, a first preset parameter of a first target camera corresponding to the first target sub-block is adjusted.

6. The method according to any one of claims 3 to 5, characterized in that: The adjusting camera parameters of at least one camera in the multi-camera system based on the difference information between the point cloud model and the target object further includes: After adjusting the first preset parameter of the first target camera based on the size difference sub-information, reacquiring a plurality of new images of the target object obtained by simultaneously photographing at least some of the cameras in the multi-camera system; Reconstructing a new point cloud model of the target object based on the multiple new images, and determining new difference information between the new point cloud model and the target object; When it is determined based on the size difference threshold that new size difference sub-information in the new difference information does not meet a first preset condition, camera parameters of at least one camera in the multi-camera system are adjusted based on the new size difference sub-information.

7. The method according to claim 6, characterized in that The difference information includes color difference sub-information between the point cloud model and the target object; The adjusting camera parameters of at least one camera in the multi-camera system based on the difference information between the point cloud model and the target object further includes: When it is determined based on the size difference threshold that the new size difference sub-information in the new difference information satisfies a first preset condition, obtaining a color difference threshold; Determining a second target camera in the multi-camera system that needs to have its parameters adjusted based on the color difference sub-information between the point cloud model and the target object, and the color difference threshold; Based on the color difference sub-information, a second preset parameter of the second target camera is adjusted.

8. The method according to claim 1, characterized in that The target object includes at least one sub-block; the color difference sub-information includes second difference sub-information corresponding to each sub-block; wherein the second difference sub-information is used to characterize the difference information between the color information of the corresponding sub-block in the point cloud model and the real color information.

9. The method according to claim 8, characterized in that The determining, based on the color difference sub-information between the point cloud model and the target object, and the color difference threshold, of a second target camera in the multi-camera system that needs to have its parameters adjusted includes: Taking the sub-block whose difference value corresponding to the second difference sub-information is greater than the color difference threshold as the second target sub-block; Determine a camera corresponding to the second target sub-block, and use the determined camera as a second target camera corresponding to the second target sub-block; The adjusting the second preset parameter of the second target camera based on the color difference sub-information includes: Based on the second difference sub-information corresponding to the second target sub-block, a second preset parameter of a second target camera corresponding to the second target sub-block is adjusted.

10. The method according to claim 9, characterized in that The adjusting camera parameters of at least one camera in the multi-camera system based on the difference information between the point cloud model and the target object further includes: After adjusting the second preset parameter of the second target camera based on the color difference sub-information, reacquiring a plurality of new images obtained by simultaneously photographing the target object by at least some cameras in the multi-camera system; Reconstructing a new point cloud model of the target object based on the multiple new images, and determining new difference information between the new point cloud model and the target object; When it is determined based on the color difference threshold that the new color difference sub-information in the new difference information does not satisfy the second preset condition, the second preset parameter of the second target camera is adjusted based on the new color difference sub-information.

11. The method according to claim 1, characterized in that: Different cameras in the multi-camera system have different shooting angles for the target object, and a target shooting angle obtained by superimposing the shooting angles of each camera is an omnidirectional shooting angle corresponding to the target object.

12. The method according to claim 1, characterized in that The distance between each camera and the target object satisfies a preset condition; wherein the preset condition includes that the shooting field of view of each camera for the target object forms a sphere or annulus, and the target object is located at a preset position within the sphere or the annulus, so that the similarity of the light reflected by the target object to each camera is higher than the preset similarity.

13. A multi-camera system calibration device, characterized in that: include: An image acquisition module, used to acquire multiple images of a target object obtained by at least some cameras simultaneously photographing the target object in a multi-camera system; A modeling module, used for constructing a point cloud model of the target object based on the multiple images; an adjustment module, configured to adjust camera parameters of at least one camera in the multi-camera system based on difference information between the point cloud model and the target object; the difference information comprising color difference sub-information between the point cloud model and the target object; The adjustment module is specifically used for: Get the color difference threshold; Determining a second target camera in the multi-camera system that needs to have its parameters adjusted based on the color difference sub-information between the point cloud model and the target object, and the color difference threshold; Based on the color difference sub-information, a second preset parameter of the second target camera is adjusted.

14. A multi-camera system calibration system, characterized in that: It includes a plurality of cameras, a camera parameter adjustment component and a target object; the target object is arranged within a target shooting field of view formed by the plurality of cameras; At least some of the multiple cameras are used to simultaneously capture images of the target object, and send the captured images to the camera parameter adjustment component; The camera parameter adjustment component is used to adjust parameters of at least one camera among the multiple cameras according to the multi-camera system calibration method according to any one of claims 1 to 12.

15. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate via the bus, and when the machine-readable instructions are executed by the processor, the steps of the multi-camera system calibration method according to any one of claims 1 to 12 are performed.

16. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the multi-camera system calibration method according to any one of claims 1 to 12 are executed.

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