A method, device, medium and electronic device for constructing a multi-camera measurement system

Abstract

The embodiments of the present application disclose a method, device, medium and electronic device for constructing a multi-camera measurement system, which relates to the field of three-dimensional measurement technology, including: calibrating the intrinsic parameters of several cameras to obtain calibrated intrinsic parameters; calibrating the extrinsic parameters of several cameras to obtain calibrated extrinsic parameters; converting the calibrated extrinsic parameters to the same coordinate system based on a common conversion point to obtain converted extrinsic parameters; constructing a multi-camera measurement system based on the calibrated intrinsic parameters and the converted extrinsic parameters. The present application uses several cameras to achieve full coverage of the measurement field to avoid the reduction in efficiency caused by a single measurement device, and then calibrates the external parameters, adjusts the posture and position relationship between each camera, and converts all the calibrated extrinsic parameters to the same coordinate system through a common conversion point, thereby reducing the transmission error between cameras and improving the accuracy of camera networking and positioning, thereby constructing a high-precision multi-camera measurement system to improve the measurement quality of large-size parts.

Description

Technical Field

[0001] The present application relates to the field of three-dimensional measurement technology, and in particular to a method, device, medium and electronic device for constructing a multi-camera measurement system. Background Art

[0002] In the field of aviation manufacturing, large parts, sections and complete machines need to be measured with high precision to determine whether they meet the manufacturing and design requirements. At present, large parts are mainly measured by three-dimensional coordinate measuring machines and laser trackers to achieve relatively sparse three-dimensional point cloud sampling. However, the quality of existing measurement methods for the measurement of large-sized parts is relatively low, which is specifically manifested in the following aspects: a single measuring device has the problem of low measurement efficiency, and due to the larger external dimensions of sections and complete machines, it is more difficult to obtain dense three-dimensional point cloud data, and the measurement data error is relatively large. Summary of the invention

[0003] The main purpose of the present application is to provide a method, device, medium and electronic equipment for constructing a multi-camera measurement system, aiming to solve the problem of low quality of measurement of large-size parts in the prior art.

[0004] To achieve the above objectives, the technical solutions adopted in the embodiments of the present application are as follows:

[0005] In a first aspect, an embodiment of the present application provides a method for constructing a multi-camera measurement system, comprising the following steps:

[0006] Calibrate the intrinsic parameters of a plurality of cameras to obtain calibrated intrinsic parameters; wherein the plurality of cameras cover a measurement field;

[0007] Calibrate the extrinsic parameters of several cameras to obtain calibrated extrinsic parameters;

[0008] The calibrated extrinsic parameters are converted to the same coordinate system based on the common conversion point to obtain the converted extrinsic parameters;

[0009] A multi-camera measurement system is constructed based on calibrating intrinsic parameters and converting extrinsic parameters.

[0010] In a possible implementation manner of the first aspect, calibrating the extrinsic parameters of a plurality of cameras, before obtaining the calibrated extrinsic parameters, the method for constructing a multi-camera measurement system further includes:

[0011] According to the marking point parameters, a coplanar condition is obtained; wherein the marking point parameters are obtained based on photographing the marking points on the same surface by a plurality of cameras;

[0012] Calibrate the external parameters of several cameras to obtain the calibrated external parameters, including:

[0013] According to the coplanar condition, the extrinsic parameters of several cameras are calibrated to obtain the calibrated extrinsic parameters.

[0014] In a possible implementation manner of the first aspect, after calibrating the intrinsic parameters of the plurality of cameras and obtaining the calibrated intrinsic parameters, the method for constructing a multi-camera measurement system further includes:

[0015] According to the finite element model and coordinate difference of the camera target surface, the pixel points of the reverse projection of the space point are compensated by using the bilinear interpolation method to correct the calibration intrinsic parameters and obtain the first calibration intrinsic parameters;

[0016] Based on the calibration of intrinsic parameters and conversion of extrinsic parameters, a multi-camera measurement system is constructed, including:

[0017] Based on the first calibration intrinsic parameters and the converted extrinsic parameters, a multi-camera measurement system is constructed.

[0018] In a possible implementation of the first aspect, according to the finite element model and coordinate difference of the camera target surface, a bilinear interpolation method is used to compensate the pixel points of the reverse projection of the space point to correct the calibration intrinsic parameter. Before obtaining the first calibration intrinsic parameter, the multi-camera measurement system construction method further includes:

[0019] According to the calibration internal parameters, the spatial points are obtained;

[0020] The spatial point is reversely projected to the pixel point to obtain the reverse-projected pixel point of the spatial point.

[0021] In a possible implementation of the first aspect, according to the finite element model and coordinate difference of the camera target surface, a bilinear interpolation method is used to compensate the pixel points of the reverse projection of the space point to correct the calibration intrinsic parameter. Before obtaining the first calibration intrinsic parameter, the multi-camera measurement system construction method further includes:

[0022] The coordinate difference is obtained according to the difference between the pixel point of the reverse projection of the spatial point and the actual pixel.

[0023] In a possible implementation of the first aspect, according to the finite element model and coordinate difference of the camera target surface, a bilinear interpolation method is used to compensate the pixel points of the reverse projection of the space point to correct the calibration intrinsic parameter. Before obtaining the first calibration intrinsic parameter, the multi-camera measurement system construction method further includes:

[0024] Divide the camera target surface to obtain several grids;

[0025] Based on the distance weighted sum algorithm, the image plane errors of the virtual points on the grid are calculated to obtain the finite element model of the camera target surface.

[0026] In a possible implementation manner of the first aspect, the intrinsic parameters of the plurality of cameras are calibrated, and before the calibrated intrinsic parameters are obtained, the method for constructing a multi-camera measurement system further includes:

[0027] Set up several cameras in the measurement field;

[0028] The cameras are adjusted so that the position to be measured within the measurement field is covered by the fields of view of at least two cameras, and the overlap of the fields of view of the cameras is greater than 60 percent.

[0029] In a second aspect, an embodiment of the present application provides a multi-camera measurement system construction device, including:

[0030] A first calibration module, the first calibration module is used to calibrate the intrinsic parameters of a plurality of cameras to obtain calibrated intrinsic parameters; wherein the plurality of cameras cover a measurement field;

[0031] A second calibration module, the second calibration module is used to calibrate the extrinsic parameters of a plurality of cameras to obtain calibrated extrinsic parameters;

[0032] A conversion module, which is used to convert the calibration extrinsic parameters into the same coordinate system based on a common conversion point to obtain conversion extrinsic parameters;

[0033] Building Module,The building module is used to build a multi-camera measurement system based on calibrating intrinsic parameters and converting extrinsic parameters.

[0034] In a third aspect, an embodiment of the present application provides a computer-readable storage medium storing a computer program. When the computer program is loaded and executed by a processor, the method for constructing a multi-camera measurement system provided in any one of the first aspects above is implemented.

[0035] In a fourth aspect, an embodiment of the present application provides an electronic device, including a processor and a memory, wherein:

[0036] The memory is used to store computer programs;

[0037] The processor is used to load and execute a computer program so that the electronic device executes the multi-camera measurement system construction method provided in any one of the first aspects above.

[0038] Compared with the prior art, the beneficial effects of this application are:

[0039] The embodiment of the present application proposes a method, device, medium and electronic device for constructing a multi-camera measurement system, the method comprising: calibrating the intrinsic parameters of several cameras to obtain calibrated intrinsic parameters; wherein several cameras cover the measurement field; calibrating the extrinsic parameters of several cameras to obtain calibrated extrinsic parameters; converting the calibrated extrinsic parameters to the same coordinate system based on a common conversion point to obtain converted extrinsic parameters; constructing a multi-camera measurement system based on the calibrated intrinsic parameters and the converted extrinsic parameters. The present application achieves full coverage of the measurement field by setting several cameras, avoiding the reduction in efficiency caused by a single measurement device, first calibrating the intrinsic parameters of the camera to improve the measurement accuracy of each camera itself, and then calibrating the external parameters to adjust the posture and position relationship between each camera, and through a common conversion point, converting all calibrated extrinsic parameters to the same coordinate system, reducing the transmission error between cameras, and further improving the accuracy of camera networking and positioning, and thereby constructing a high-precision multi-camera measurement system to improve the measurement quality of large-size parts. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A schematic diagram of the structure of an electronic device of a hardware operating environment involved in an embodiment of the present application;

[0041] Figure 2 A schematic diagram of a process for constructing a multi-camera measurement system provided in an embodiment of the present application;

[0042] Figure 3 A schematic diagram of the array layout of multiple cameras in the method for constructing a multi-camera measurement system provided in an embodiment of the present application;

[0043] Figure 4 A schematic diagram of the bilinear interpolation method in the method for constructing a multi-camera measurement system provided in an embodiment of the present application;

[0044] Figure 5 A schematic diagram of a module of a multi-camera measurement system construction device provided in an embodiment of the present application;

[0045] Markings in the figure: 101 - processor, 102 - communication bus, 103 - network interface, 104 - user interface, 105 - memory. DETAILED DESCRIPTION

[0046] It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0047] The main solution of the embodiment of the present application is: calibrate the intrinsic parameters of several cameras to obtain calibrated intrinsic parameters; wherein the several cameras cover the measurement field; calibrate the extrinsic parameters of several cameras to obtain calibrated extrinsic parameters; based on a common transformation point, the calibrated extrinsic parameters are transformed into the same coordinate system to obtain transformed extrinsic parameters; based on the calibrated intrinsic parameters and the transformed extrinsic parameters, a multi-camera measurement system is constructed.

[0048] In the field of aviation manufacturing, large parts, sections and complete machines need to be measured with high precision to determine whether they meet the manufacturing and design requirements, and to further ensure the aerodynamic performance of the aircraft. At present, large parts are mainly measured by three-dimensional coordinate measuring machines and laser trackers to achieve relatively sparse three-dimensional point cloud sampling. However, these single measuring devices have the problem of low measurement efficiency, and it is difficult to achieve high-precision dense point cloud sampling to optimize the processing technology, and it is also difficult to meet the high-precision and high-efficiency requirements in the aircraft manufacturing process. At the same time, due to the larger external dimensions of sections and complete machines, it is more difficult to obtain dense three-dimensional point cloud data, and the measurement data error is relatively large.

[0049] With the continuous development of 3D measurement technology and equipment, combined measurement systems combining multiple measurement equipment are gradually used in the field of aviation manufacturing to achieve large-scale measurement. Among them, the combined measurement system formed by photogrammetry and structural scanning is currently the most widely used method. The structured light system scans local 3D point cloud information. Photogrammetry uses multiple cameras to locate the local scanning system and complete the coordinate system, thereby achieving high-precision and high-efficiency large-scale measurement.

[0050] Publication No. CN109990701A proposes a 3D measurement system for large complex curved surfaces. The method mainly combines landmark points, a robotic arm and structured light scanning to build a combined measurement system, and unifies the coordinate system by positioning the structured light scanning with landmark points, realizes the coordinate system conversion of the 3D point cloud data of the local scan, and then obtains the full-view 3D point cloud data.

[0051] Publication No. CN113432550A proposes a phase-matching-based 3D measurement and splicing method for large-size parts. This method mainly uses the grating phase principle and combines the matching features projected by the local scanning system to match the feature points of the local scanning system and the global measurement system, and then reconstructs the 3D corresponding points of the local measurement coordinate system and the global measurement coordinate system. This method constructs an optimization function and combines the feature matching points, 3D corresponding points, and the internal parameters of the local and global measurement systems to obtain the conversion relationship between the local measurement coordinate system and the global coordinate system, thereby realizing the splicing of large-size point cloud data.

[0052] The above method does not pay attention to the characteristics of application to large-size parts, and mainly starts from the extraction of point data during the measurement process. Different from the above method, this application mainly starts from the accuracy of camera networking in the measurement system, improves the quality based on measurement, and provides a solution. By setting up several cameras to achieve full coverage of the measurement field, it avoids the efficiency reduction caused by a single measurement device. The camera's internal parameters are calibrated first to improve the measurement accuracy of each camera itself, and then the external parameters are calibrated to adjust the posture and position relationship between each camera. Through a common conversion point, all calibrated external parameters are converted to the same coordinate system, reducing the transmission error between cameras and further improving the accuracy of camera networking positioning. In this way, a high-precision multi-camera measurement system is constructed to improve the measurement quality of large-size parts.

[0053] See attached Figure 1 , attached Figure 1 This is a schematic diagram of the structure of an electronic device of the hardware operating environment involved in the embodiment of the present application. The electronic device may include: a processor 101, such as a central processing unit (CPU), a communication bus 102, a user interface 104, a network interface 103, and a memory 105. Among them, the communication bus 102 is used to realize the connection and communication between these components. The user interface 104 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the user interface 104 may also include a standard wired interface and a wireless interface. The network interface 103 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (WIreless-FIdelity, WI-FI) interface). The memory 105 may optionally be a storage device independent of the aforementioned processor 101. The memory 105 may be a high-speed random access memory (RAM) memory, or it may be a stable non-volatile memory (NVM), such as at least one disk storage; the processor 101 may be a general-purpose processor, including a central processing unit, a network processor, etc., or it may be a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component.

[0054] Those skilled in the art will appreciate that Figure 1 The structure shown in the figure does not constitute a limitation on the electronic device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0055] As attached Figure 1As shown, the memory 105 as a storage medium may include an operating system, a network communication module, a user interface module, and a multi-camera measurement system construction device.

[0056] In the attached Figure 1 In the electronic device shown, the network interface 103 is mainly used for data communication with a network server; the user interface 104 is mainly used for data interaction with a user; the processor 101 and the memory 105 in the present application can be set in the electronic device, and the electronic device calls the multi-camera measurement system construction device stored in the memory 105 through the processor 101, and executes the multi-camera measurement system construction method provided in the embodiment of the present application.

[0057] See attached Figure 2 Based on the hardware device of the aforementioned embodiment, the embodiment of the present application provides a method for constructing a multi-camera measurement system, comprising the following steps:

[0058] S10: Calibrate the intrinsic parameters of a plurality of cameras to obtain calibrated intrinsic parameters; wherein the plurality of cameras cover a measurement field.

[0059] In the specific implementation process, the calibration of the camera's intrinsic parameters can be considered as a process of solving equations, that is, after knowing the spatial point and its coordinates in the pixel coordinate system, the camera's intrinsic parameters are solved according to the conversion relationship between the world coordinate system and the various coordinate systems inside the camera, thereby achieving the purpose of intrinsic parameter calibration. This embodiment takes 16 cameras as an example for explanation, as shown in the attached figure. Figure 3 As shown, 16 cameras are networked through 8 columns, two cameras are arranged on each column, and the columns are arranged in two rows, with 4 columns in each row, and the distance between the columns depends on the measurement object. The target surface of the camera is 4096*3000, the pixel size is 3.45μm, and the lens is a fixed-focus lens with a focal length of 16mm. The number of cameras in each layer can be dynamically adjusted according to the actual working conditions, measurement accuracy and size, and in order to achieve full coverage of the measurement field, the camera positions are arranged so that their field of view can meet the needs, that is, the intrinsic parameters of several cameras are calibrated. Before obtaining the calibrated intrinsic parameters, the multi-camera measurement system construction method also includes:

[0060] Set up several cameras in the measurement field;

[0061] The cameras are adjusted so that the position to be measured within the measurement field is covered by the fields of view of at least two cameras, and the overlap of the fields of view of the cameras is greater than 60 percent.

[0062] In one embodiment, according to the finite element model and coordinate difference of the camera target surface, a bilinear interpolation method is used to compensate the pixel points of the reverse projection of the space point to correct the calibration intrinsic parameter. Before obtaining the first calibration intrinsic parameter, the multi-camera measurement system construction method further includes:

[0063] Divide the camera target surface to obtain several grids;

[0064] Based on the distance weighted sum algorithm, the image plane errors of the virtual points on the grid are calculated to obtain the finite element model of the camera target surface.

[0065] In the specific implementation process, the target surface of the camera is virtually divided into 24×11 grids at a spacing of 0.5 mm, and the image plane error of each virtual point is calculated by distance weighted summation, and then a finite element model is constructed. The weighted summation considers the proportion of the element, which can also be understood as the degree of importance, while the distance weighted summation measures the size of the proportion according to the relative distance.

[0066] In one embodiment, after calibrating the intrinsic parameters of a plurality of cameras and obtaining the calibrated intrinsic parameters, the method for constructing a multi-camera measurement system further includes:

[0067] According to the finite element model of the camera target surface and the coordinate difference, the bilinear interpolation method is used to compensate the pixel points of the reverse projection of the space point to correct the calibration intrinsic parameters and obtain the first calibration intrinsic parameters.

[0068] Based on the above steps, a multi-camera measurement system is constructed based on calibrating intrinsic parameters and converting extrinsic parameters, including:

[0069] Based on the first calibration intrinsic parameters and the converted extrinsic parameters, a multi-camera measurement system is constructed.

[0070] In the specific implementation process, since the traditional camera intrinsic parameter calibration method is difficult to meet the requirements of photogrammetry accuracy control in a large size range, this embodiment proposes a bilinear interpolation calibration method, and adds a finite element model on the basis of the traditional intrinsic parameter calibration to further improve the accuracy of camera intrinsic parameter calibration. It can be seen from the three-point collinearity equation of camera imaging:

[0071]

[0072] In the formula, Δx, Δy represent distortion parameters; x0, y0 represent the image coordinate center; f represents the focal length of the lens; (X S ,Y S ,Z S ) represents the position coordinates of the camera in the ground coordinate system; (a1, a2, a3, b1, b2, b3, c1, c2, c3) represents the direction cosines in the rotation matrix composed of the camera attitude angle. It will directly affect the coordinate error of the three-dimensional space point (X, Y, Z), and its mathematical model can be expressed as:

[0073]

[0074] Where k1, k2, k3 represent radial distortion; p1, p2 represent tangential distortion; b1, b2 represent image plane distortion, and the Brown model is used to perform preliminary correction for the distortion. The coordinates of the three-dimensional space points are calculated using the above-mentioned calibrated parameters, and the three-dimensional space points are reversely projected to the pixel points, and compared with the actual pixels to obtain the coordinate difference. That is: according to the finite element model and coordinate difference of the camera target surface, the bilinear interpolation method is used to compensate the pixel points of the reverse projection of the space points to correct the calibration internal parameters. Before obtaining the first calibration internal parameters, the multi-camera measurement system construction method also includes:

[0075] The coordinate difference is obtained according to the difference between the pixel point of the reverse projection of the spatial point and the actual pixel.

[0076] Generate virtual points corresponding to the size of the camera CCD, and use distance weighted sum to calculate the image plane error, and then obtain the finite element model. Combined with the obtained finite element model, the error compensation of the back-projected pixel points is performed through bilinear interpolation, and the compensated pixel points are calculated, as shown in the attached figure. Figure 4 As shown, the high-precision calibration of the camera internal parameters in the network is realized. That is, according to the finite element model and coordinate difference of the camera target surface, the bilinear interpolation method is used to compensate the pixel points of the reverse projection of the space point to correct the calibration internal parameters. Before obtaining the first calibration internal parameters, the multi-camera measurement system construction method also includes:

[0077] According to the calibration internal parameters, the spatial points are obtained;

[0078] The spatial point is reversely projected to the pixel point to obtain the reverse-projected pixel point of the spatial point.

[0079] S20: Calibrate extrinsic parameters of several cameras to obtain calibrated extrinsic parameters.

[0080] In the specific implementation process, after the calibration of the camera internal parameters in the network is completed, it is necessary to calibrate the external parameters of these cameras to determine the posture and position relationship between the cameras, and calibrate the overall external parameters of all cameras in the network through the coplanar condition, so as to achieve high-precision multi-camera external parameter calibration and provide high-precision positioning information for the local scanning system in the network. Among them, the coplanar condition can be obtained by using multiple cameras to simultaneously shoot the same surface landmarks, that is:

[0081] Before calibrating the external parameters of several cameras and obtaining the calibrated external parameters, the method for constructing a multi-camera measurement system further includes:

[0082] According to the marking point parameters, the coplanar condition is obtained; wherein the marking point parameters are obtained based on photographing the marking points on the same surface by a plurality of cameras.

[0083] Based on the above steps, the external parameters of several cameras are calibrated to obtain the calibrated external parameters, including:

[0084] According to the coplanar condition, the extrinsic parameters of several cameras are calibrated to obtain the calibrated extrinsic parameters.

[0085] S30: Convert the calibration extrinsic parameters to the same coordinate system based on the common conversion point to obtain converted extrinsic parameters.

[0086] In the specific implementation process, although the accuracy of the calibration of intrinsic parameters is improved, the calibration of extrinsic parameters between two cameras will introduce transmission errors due to the use of multi-camera networking. In order to reduce this error and improve the calibration accuracy, the camera extrinsic parameters are calculated through overall calibration, and then the extrinsic parameters of the multi-camera array are unified to the same coordinate system by setting a common transformation point. The converted parameters are the converted extrinsic parameters, which greatly reduces the transmission error caused by the calibration of the extrinsic parameters between two cameras.

[0087] S40: Construct a multi-camera measurement system based on calibrating intrinsic parameters and converting extrinsic parameters.

[0088] In the specific implementation process, the intrinsic parameters of the camera were calibrated to obtain the calibrated internal parameters, and the external parameters were calibrated and converted to obtain the converted external parameters. When the internal and external parameters of the camera were calibrated, the positioning accuracy of the multi-camera network was guaranteed, and the construction of the multi-camera measurement system was completed.

[0089] In this embodiment, a number of cameras are set up to achieve full coverage of the measurement field, avoiding the reduction in efficiency caused by a single measurement device. The intrinsic parameters of the camera are calibrated first to improve the measurement accuracy of each camera itself, and then the external parameters are calibrated to adjust the posture and position relationship between each camera. Through a common conversion point, all the calibrated external parameters are converted to the same coordinate system, reducing the transmission error between cameras and further improving the accuracy of camera networking and positioning. In this way, a high-precision multi-camera measurement system is constructed to improve the measurement quality of large-size parts.

[0090] See attached Figure 5 Based on the same inventive concept as in the above-mentioned embodiment, the embodiment of the present application further provides a multi-camera measurement system construction device, which includes:

[0091] A first calibration module, the first calibration module is used to calibrate the intrinsic parameters of a plurality of cameras to obtain calibrated intrinsic parameters; wherein the plurality of cameras cover a measurement field;

[0092] A second calibration module, the second calibration module is used to calibrate the extrinsic parameters of a plurality of cameras to obtain calibrated extrinsic parameters;

[0093] A conversion module, which is used to convert the calibration extrinsic parameters into the same coordinate system based on a common conversion point to obtain conversion extrinsic parameters;

[0094] Building Module,The building module is used to build a multi-camera measurement system based on calibrating intrinsic parameters and converting extrinsic parameters.

[0095] Those skilled in the art should understand that the division of the various modules in the embodiment is merely a division of logical functions, and in actual application, all or part of them can be integrated into one or more actual carriers, and these modules can be implemented entirely in the form of software called by a processing unit, or entirely in the form of hardware, or in the form of a combination of software and hardware. It should be noted that each module in the multi-camera measurement system construction device in this embodiment corresponds one-to-one to each step in the multi-camera measurement system construction method in the aforementioned embodiment. Therefore, the specific implementation of this embodiment can refer to the implementation of the aforementioned multi-camera measurement system construction method, which will not be repeated here.

[0096] Based on the same inventive concept as in the aforementioned embodiment, an embodiment of the present application further provides a computer-readable storage medium storing a computer program. When the computer program is loaded and executed by a processor, a multi-camera measurement system construction method as provided in the embodiment of the present application is implemented.

[0097] Based on the same inventive concept as in the above-mentioned embodiment, an embodiment of the present application further provides an electronic device, including a processor and a memory, wherein:

[0098] The memory is used to store computer programs;

[0099] The processor is used to load and execute a computer program so that the electronic device executes the multi-camera measurement system construction method provided in the embodiment of the present application.

[0100] In some embodiments, the computer readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disk, or CD-ROM; or various devices including one or any combination of the above memories. The computer may be various computing devices including intelligent terminals and servers.

[0101] In some embodiments, executable instructions may be in the form of a program, software, software module, script or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as a stand-alone program or as a module, component, subroutine or other unit suitable for use in a computing environment.

[0102] As an example, executable instructions may, but need not, correspond to a file in a file system, may be stored as part of a file that stores other programs or data, such as in one or more scripts in a HyperText Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files storing one or more modules, subroutines, or code portions).

[0103] By way of example, executable instructions may be deployed to be executed on one computing device, or on multiple computing devices located at one site, or on multiple computing devices distributed across multiple sites and interconnected by a communication network.

[0104] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0105] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0106] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory / random access memory, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a multimedia terminal device (which can be a mobile phone, a computer, a television receiver, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0107] In summary, the present application provides a method, device, medium and electronic device for constructing a multi-camera measurement system, the method comprising: calibrating the intrinsic parameters of several cameras to obtain calibrated intrinsic parameters; wherein several cameras cover the measurement field; calibrating the extrinsic parameters of several cameras to obtain calibrated extrinsic parameters; converting the calibrated extrinsic parameters to the same coordinate system based on a common conversion point to obtain converted extrinsic parameters; constructing a multi-camera measurement system based on the calibrated intrinsic parameters and the converted extrinsic parameters. The present application achieves full coverage of the measurement field by setting up several cameras, avoiding the reduced efficiency caused by a single measurement device, first calibrating the intrinsic parameters of the camera to improve the measurement accuracy of each camera itself, and then calibrating the external parameters to adjust the posture and position relationship between each camera, and through a common conversion point, converting all the calibrated extrinsic parameters to the same coordinate system, reducing the transmission error between cameras, and further improving the accuracy of camera networking and positioning, and thereby constructing a high-precision multi-camera measurement system to improve the measurement quality of large-size parts.

[0108] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A method for constructing a multi-camera measurement system, characterized in that: The following steps are involved: Calibrate the intrinsic parameters of a plurality of cameras to obtain calibrated intrinsic parameters; wherein the plurality of cameras cover a measurement field, and the calibration of the intrinsic parameters is performed based on spatial points; Calibrate the extrinsic parameters of the plurality of cameras to obtain calibrated extrinsic parameters; wherein the calibration of the extrinsic parameters is performed based on the identification points; before calibrating the extrinsic parameters of the plurality of cameras to obtain the calibrated extrinsic parameters, the multi-camera measurement system construction method further includes: According to the marking point parameters, a coplanar condition is obtained; wherein the marking point parameters are obtained based on the marking points on the same surface photographed by a plurality of the cameras; The step of calibrating the external parameters of the plurality of cameras to obtain the calibrated external parameters includes: Calibrate the extrinsic parameters of the plurality of cameras according to the coplanar condition to obtain calibrated extrinsic parameters; The calibration extrinsic parameters are converted into the same coordinate system based on the common conversion point to obtain the converted extrinsic parameters; Based on the calibrated intrinsic parameters and the converted extrinsic parameters, a multi-camera measurement system is constructed; after the intrinsic parameters of the plurality of cameras are calibrated to obtain the calibrated intrinsic parameters, the multi-camera measurement system construction method further includes: According to the finite element model of the camera target surface and the coordinate difference, a bilinear interpolation method is used to compensate the pixel points of the reverse projection of the spatial point to correct the calibration intrinsic parameter to obtain a first calibration intrinsic parameter; The method of constructing a multi-camera measurement system based on the calibration intrinsic parameters and the conversion extrinsic parameters includes: constructing a multi-camera measurement system based on the first calibration intrinsic parameter and the conversion extrinsic parameter; According to the finite element model and coordinate difference of the camera target surface, the bilinear interpolation method is used to compensate the pixel points of the reverse projection of the space point to correct the calibration intrinsic parameter. Before obtaining the first calibration intrinsic parameter, the multi-camera measurement system construction method also includes: According to the calibration intrinsic parameters, obtaining the spatial point; The spatial point is reversely projected to a pixel point to obtain a pixel point of the reverse projection of the spatial point.

2. The method for constructing a multi-camera measurement system according to claim 1, characterized in that: According to the finite element model and coordinate difference of the camera target surface, the bilinear interpolation method is used to compensate the pixel points of the reverse projection of the space point to correct the calibration intrinsic parameter. Before obtaining the first calibration intrinsic parameter, the multi-camera measurement system construction method also includes: The coordinate difference is obtained according to the difference between the pixel point of the reverse projection of the spatial point and the actual pixel.

3. The method for constructing a multi-camera measurement system according to claim 1, characterized in that: According to the finite element model and coordinate difference of the camera target surface, the bilinear interpolation method is used to compensate the pixel points of the reverse projection of the space point to correct the calibration intrinsic parameter. Before obtaining the first calibration intrinsic parameter, the multi-camera measurement system construction method also includes: Dividing the camera target surface to obtain a plurality of grids; Based on a distance weighted sum algorithm, the image plane errors of the virtual points on the grid are calculated to obtain a finite element model of the camera target surface.

4. The method for constructing a multi-camera measurement system according to claim 1, characterized in that: Before calibrating the intrinsic parameters of the plurality of cameras to obtain the calibrated intrinsic parameters, the method for constructing a multi-camera measurement system further includes: Setting a plurality of the cameras in the measurement field; The cameras are adjusted so that the position to be measured within the measurement field is covered by the fields of view of at least two of the cameras, and the overlap of the fields of view of the cameras is greater than 60 percent.

5. A multi-camera measurement system construction device, characterized in that: include: A first calibration module, the first calibration module is used to calibrate the intrinsic parameters of a plurality of cameras to obtain calibrated intrinsic parameters; wherein the plurality of cameras cover a measurement field, and the calibration of the intrinsic parameters is performed based on spatial points; A second calibration module, wherein the second calibration module is used to calibrate the external parameters of the plurality of cameras to obtain calibrated external parameters; wherein the calibration of the external parameters is performed based on the identification points; before the calibrating the external parameters of the plurality of cameras to obtain the calibrated external parameters, the module further includes: According to the marking point parameters, a coplanar condition is obtained; wherein the marking point parameters are obtained based on the marking points on the same surface photographed by a plurality of the cameras; The step of calibrating the external parameters of the plurality of cameras to obtain the calibrated external parameters includes: Calibrate the extrinsic parameters of the plurality of cameras according to the coplanar condition to obtain calibrated extrinsic parameters; A conversion module, the conversion module is used to convert the calibration extrinsic parameters into the same coordinate system based on a common conversion point to obtain conversion extrinsic parameters; A construction module, wherein the construction module is used to construct a multi-camera measurement system based on the calibration intrinsic parameters and the conversion extrinsic parameters; after calibrating the intrinsic parameters of several cameras and obtaining the calibrated intrinsic parameters, the method further comprises: According to the finite element model of the camera target surface and the coordinate difference, a bilinear interpolation method is used to compensate the pixel points of the reverse projection of the spatial point to correct the calibration intrinsic parameter to obtain a first calibration intrinsic parameter; The method of constructing a multi-camera measurement system based on the calibration intrinsic parameters and the conversion extrinsic parameters includes: constructing a multi-camera measurement system based on the first calibration intrinsic parameter and the conversion extrinsic parameter; According to the finite element model of the camera target surface and the coordinate difference, the pixel points of the reverse projection of the space point are compensated by using the bilinear interpolation method to correct the calibration intrinsic parameter. Before obtaining the first calibration intrinsic parameter, the method further includes: According to the calibration intrinsic parameters, obtaining the spatial point; The spatial point is reversely projected to a pixel point to obtain a pixel point of the reverse projection of the spatial point.

6. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is loaded and executed by the processor, the multi-camera measurement system construction method according to any one of claims 1 to 4 is implemented.

7. An electronic device, characterized in that: comprising a processor and a memory, wherein: The memory is used to store computer programs; The processor is used to load and execute the computer program so that the electronic device executes the multi-camera measurement system construction method according to any one of claims 1 to 4.

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