CN115841541A - Method and device for constructing 3D panoramic all-around model of vehicle - Google Patents
Method and device for constructing 3D panoramic all-around model of vehicle Download PDFInfo
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- CN115841541A CN115841541A CN202211062587.XA CN202211062587A CN115841541A CN 115841541 A CN115841541 A CN 115841541A CN 202211062587 A CN202211062587 A CN 202211062587A CN 115841541 A CN115841541 A CN 115841541A
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Abstract
The invention relates to a method and a device for constructing a 3D panoramic all-around model of a vehicle, wherein the method comprises the following steps: acquiring a plurality of images shot by vehicle-mounted cameras arranged at different positions on a vehicle of the vehicle, and calibrating internal and external parameters of each vehicle-mounted camera according to the images; matching the image shot by each vehicle-mounted camera with a preset 3D model to construct a plurality of initial 3D models; calculating a pixel coordinate corresponding relation table of each initial 3D model and an image shot by the corresponding vehicle-mounted camera according to the calibrated internal and external parameters of each vehicle-mounted camera; performing texture binding on each initial 3D model based on the pixel coordinate corresponding relation table; and synthesizing the plurality of bound initial 3D models to obtain the vehicle-mounted 3D panoramic all-around model. According to the invention, the construction of the 3D panoramic view model is realized through the pixel relation calculation between the images shot by the plurality of vehicle-mounted cameras and the 3D model, and the problems of distortion and small view field range of 2D panoramic view imaging are solved.
Description
Technical Field
The invention belongs to the technical field of image data processing, and particularly relates to a method and a device for constructing a 3D panoramic all-around view model of a vehicle.
Background
The image stitching technology is a hot point of research in the field of automobile electronics in recent years, and is applied to a vehicle-mounted all-round display system. The vehicle-mounted panoramic view mainly adopts the technology that four cameras arranged on a vehicle head, a vehicle tail and two rearview mirrors are used for acquiring four images and splicing the four images into a panoramic image. Most of vehicle-mounted panoramic system products in the current stage are 2D panoramic image splicing, but the 2D panoramic imaging has the defects of certain distortion, small visual field range and the like.
Disclosure of Invention
In order to solve the problems of distortion and small visual field range of 2D panoramic imaging, a first aspect of the present invention provides a method for constructing a 3D panoramic view model of a vehicle, comprising: acquiring a plurality of images shot by vehicle-mounted cameras arranged at different positions on a vehicle of the vehicle, and calibrating internal and external parameters of each vehicle-mounted camera according to the images; matching the image shot by each vehicle-mounted camera with a preset 3D model to construct a plurality of initial 3D models; calculating a pixel coordinate corresponding relation table of each initial 3D model and an image shot by the corresponding vehicle-mounted camera according to the calibrated internal and external parameters of each vehicle-mounted camera; performing texture binding on each initial 3D model based on the pixel coordinate corresponding relation table; and synthesizing the plurality of bound initial 3D models to obtain the vehicle-mounted 3D panoramic all-around model.
In some embodiments of the present invention, the acquiring a plurality of images captured by vehicle-mounted cameras deployed at different positions on the own vehicle and performing internal and external reference calibration on each vehicle-mounted camera according to the plurality of images includes: carrying out internal reference calibration on each vehicle-mounted camera; determining the direction of a calibration plate which is subjected to external parameter calibration by each vehicle-mounted camera in a vehicle, and measuring the distance from the calibration plate to the center of the vehicle body of the vehicle; and calculating an external parameter matrix of each vehicle-mounted camera by an external parameter estimation method based on the direction of the calibration plate in the vehicle and the distance from the calibration plate to the center of the body of the vehicle.
Further, the calculating the external parameter matrix of each vehicle-mounted camera by an external parameter estimation method based on the direction of the calibration plate in the vehicle and the distance from the calibration plate to the center of the body of the vehicle comprises: determining coordinates of the corner points of the calibration plate in an image shot by the vehicle-mounted camera; and calculating an external parameter matrix of each vehicle-mounted camera according to the calibrated internal parameters, coordinates of the angular points of the calibration plate in the images shot by the vehicle-mounted cameras, the direction of the calibration plate in the vehicle and the distance from the calibration plate to the center of the vehicle body of the vehicle.
In some embodiments of the present invention, the calculating a pixel coordinate correspondence table of each initial 3D model and an image captured by the vehicle-mounted camera corresponding to the initial 3D model according to the calibrated internal and external parameters of each vehicle-mounted camera includes: reading the vertex coordinates of each initial 3D model; calculating the coordinates of pixels in the visual angle image corresponding to each vehicle-mounted camera according to the calibrated internal and external parameters of each vehicle-mounted camera; and constructing a corresponding relation table according to the vertex coordinates of each initial 3D model and the coordinates of the pixels in the corresponding view angle image.
Further, the method for calculating the coordinates of the pixels in the view angle image corresponding to each vehicle-mounted camera according to the calibrated internal and external parameters of each vehicle-mounted camera comprises the following steps:
wherein (u, v) represents pixel coordinates in the angle-of-view image,
for each vehicle camera's internal reference matrix, < >>
For each onboard camera, the external reference matrix, (x, y, z) is the vertex coordinates of the initial 3D model.
In the above embodiment, the texture binding each initial 3D model based on the pixel coordinate correspondence table includes: based on the pixel coordinate corresponding relation table, searching a pixel value corresponding to each vertex coordinate; and traversing each pixel of the image shot by each vehicle-mounted camera to obtain pixel values corresponding to all vertexes of each initial 3D model.
In a second aspect of the present invention, there is provided a vehicle 3D panoramic view model construction apparatus, including: the acquisition module is used for acquiring a plurality of images shot by vehicle-mounted cameras arranged at different positions on a vehicle and calibrating internal and external parameters of each vehicle-mounted camera according to the images; the matching module is used for matching the image shot by each vehicle-mounted camera with a preset 3D model and constructing a plurality of initial 3D models; the calculation module is used for calculating a pixel coordinate corresponding relation table of each initial 3D model and an image shot by the corresponding vehicle-mounted camera according to the calibrated internal and external parameters of each vehicle-mounted camera; the synthesis module is used for performing texture binding on each initial 3D model based on the pixel coordinate corresponding relation table; and synthesizing the plurality of bound initial 3D models to obtain the vehicle-mounted 3D panoramic all-around model.
Further, the obtaining module includes: the calibration unit is used for carrying out internal reference calibration on each vehicle-mounted camera; the determining unit is used for determining the direction of a calibration plate which is used for performing external reference calibration by each vehicle-mounted camera in the vehicle, and measuring the distance from the calibration plate to the center of the vehicle body of the vehicle; and the calculation unit is used for calculating an external parameter matrix of each vehicle-mounted camera through an external parameter estimation method based on the direction of the calibration plate in the vehicle and the distance from the calibration plate to the center of the body of the vehicle.
In a third aspect of the present invention, there is provided an electronic device comprising: one or more processors; a storage device for storing one or more programs, which when executed by the one or more processors, cause the one or more processors to implement the method for constructing a 3D panoramic all around model of a vehicle according to the present invention provided in the first aspect.
In a fourth aspect of the present invention, a computer readable medium is provided, on which a computer program is stored, wherein the computer program, when executed by a processor, implements the vehicle 3D panoramic view model construction method provided by the present invention in the first aspect.
The invention has the beneficial effects that:
the invention provides a method for constructing a 3D panoramic all-around model of a vehicle, which comprises the following steps: acquiring a plurality of images shot by vehicle-mounted cameras arranged at different positions on a vehicle of the vehicle, and calibrating internal and external parameters of each vehicle-mounted camera according to the images; matching the image shot by each vehicle-mounted camera with a preset 3D model to construct a plurality of initial 3D models; calculating a pixel coordinate corresponding relation table of each initial 3D model and an image shot by the corresponding vehicle-mounted camera according to the calibrated internal and external parameters of each vehicle-mounted camera; performing texture binding on each initial 3D model based on the pixel coordinate corresponding relation table; and synthesizing the plurality of bound initial 3D models to obtain the vehicle-mounted 3D panoramic all-around model. Therefore, the method realizes the construction of the 3D panoramic model by calculating the pixel relation between the images shot by the plurality of vehicle-mounted cameras and the 3D model, and solves the problems of distortion and small visual field range of 2D panoramic imaging. Because the calculation of the corresponding table of the calculation model and the camera is only used for initialization or first construction, efficient mapping or conversion between pixels and vertexes can be realized by utilizing a table look-up algorithm, and the 3D panoramic fluency is high. On the other hand, the size and shape of the initial 3D model and the vehicle model can be modified arbitrarily, thereby improving the flexibility and adaptability of model construction.
Drawings
FIG. 1 is a basic flow diagram of a method of constructing a 3D panoramic all-round model of a vehicle in some embodiments of the invention;
FIG. 2 is a schematic diagram of an initial 3D model in some embodiments of the invention;
FIG. 3 is a schematic diagram of an initial 3D model after texture binding in some embodiments of the invention;
FIG. 4 is a rendering of a 3D panoramic surround view model of a vehicle in some embodiments of the invention;
FIG. 5 is a schematic structural diagram of a 3D panoramic all-around model building apparatus for a vehicle according to some embodiments of the present invention;
fig. 6 is a schematic structural diagram of an electronic device in some embodiments of the invention.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, in a first aspect of the present invention, there is provided a vehicle 3D panoramic looking-around model construction method, including: s100, acquiring a plurality of images shot by vehicle-mounted cameras arranged at different positions on a vehicle, and calibrating internal and external parameters of each vehicle-mounted camera according to the images; s200, matching images shot by each vehicle-mounted camera with a preset 3D model to construct a plurality of initial 3D models; s300, calculating a pixel coordinate corresponding relation table of each initial 3D model and an image shot by the corresponding vehicle-mounted camera according to the calibrated internal and external parameters of each vehicle-mounted camera; s400, performing texture binding on each initial 3D model based on the pixel coordinate corresponding relation table; and synthesizing the plurality of bound initial 3D models to obtain the vehicle-mounted 3D panoramic all-around model. It should be noted that, for a 3D panoramic image or a 3D panoramic view model, a plurality of images shot by vehicle-mounted cameras at different positions, corresponding to the images at their different viewing angles.
In step S100 of some embodiments of the present invention, the acquiring a plurality of images captured by vehicle-mounted cameras disposed at different positions on the own vehicle and performing internal and external reference calibration on each vehicle-mounted camera according to the plurality of images includes: s101, performing internal reference calibration on each vehicle-mounted camera; s102, determining the direction of a calibration plate for external reference calibration of each vehicle-mounted camera in a vehicle, and measuring the distance from the calibration plate to the center of the vehicle body of the vehicle; s103, calculating an external parameter matrix of each vehicle-mounted camera through an external parameter estimation method based on the direction of the calibration plate in the vehicle and the distance between the calibration plate and the center of the vehicle body of the vehicle.
Further, in step S103, the calculating an external parameter matrix of each vehicle-mounted camera by an external parameter estimation method based on the direction of the calibration plate in the vehicle and the distance from the calibration plate to the center of the body of the vehicle includes: determining coordinates of the corner points of the calibration plate in an image shot by the vehicle-mounted camera; and calculating an external parameter matrix of each vehicle-mounted camera according to the calibrated internal parameters, coordinates of the angular points of the calibration plate in the images shot by the vehicle-mounted cameras, the direction of the calibration plate in the vehicle and the distance from the calibration plate to the center of the vehicle body of the vehicle. Specifically, taking four fisheye cameras mounted on the head, the tail and two rear-view mirrors of the vehicle as an example, camera internal reference is obtained by calibrating conventional fisheye camera internal reference. And then placing the 4 calibration plates in 4 directions of the vehicle, measuring the distance from 4 angular points of the 4 calibration plates to the center of the vehicle body, finding the angular points of the 4 calibration plates on 4 pictures, and calculating the external parameter matrix of the 4 cameras by an external parameter estimation method.
Referring to fig. 2, which shows a schematic diagram of an initial 3D model, taking the above four onboard cameras as an example, it is necessary to match and crop an image captured by each onboard camera according to a preset 3D model to make 4 initial 3D models, which correspond to the captured images of the 4 onboard cameras respectively.
In step S300 of some embodiments of the present invention, the calculating a pixel coordinate correspondence table of each initial 3D model and the image captured by the corresponding onboard camera according to the calibrated internal and external parameters of each onboard camera includes: s301, reading the vertex coordinates of each initial 3D model; s302, calculating coordinates of pixels in the visual angle image corresponding to each vehicle-mounted camera according to the calibrated internal and external parameters of each vehicle-mounted camera; and S303, constructing a corresponding relation table according to the vertex coordinates of each initial 3D model and the coordinates of the pixels in the corresponding view angle image.
Further, in step S302, the calculating the coordinates of the pixels in the view angle image corresponding to each vehicle-mounted camera according to the calibrated internal and external parameters of each vehicle-mounted camera includes:
wherein (u, v) represents pixel coordinates in the angle-of-view image,
for each vehicle camera's internal reference matrix, < >>
For each vehicle camera's external reference matrix, (x, y, z) are the vertex coordinates of the initial 3D model, and s represents the perspective image.
Referring to fig. 3, in S400 of the foregoing embodiment, the texture binding each initial 3D model based on the pixel coordinate correspondence table includes: s401, searching a pixel value corresponding to each vertex coordinate based on the pixel coordinate corresponding relation table; s402, traversing each pixel of the image shot by each vehicle-mounted camera to obtain pixel values corresponding to all vertexes of each initial 3D model. And filling the pixel values into the corresponding initial 3D model to obtain the initial 3D model after texture binding (filling).
It should be noted that the initial 3D model has two parameters, namely vertex coordinates and texture coordinates, and each vertex coordinate has a corresponding texture coordinate; texture coordinates are equal to the resulting pixel coordinates (u, v) divided by the width and height of the camera image, respectively: texture coordinate x = u/image width and texture coordinate y = v/image height. The table of correspondence between pixel coordinates and vertices means that the vertex coordinates are converted into corresponding pixel coordinates according to the corresponding texture coordinates and the texture coordinates, and the pixel values mapped by the vertex coordinates are the pixel values of the corresponding pixel coordinates.
Referring to fig. 4, the obtained initial 3D models after texture binding are projected into the same coordinate system through the vertex in the initial 3D model, the same projection points are matched, merged, deduplicated (spliced), and rendered to obtain the final 3D all-around model.
Example 2
Referring to fig. 5, in a second aspect of the present invention, there is provided a vehicle 3D panoramic view model construction apparatus 1, including: the acquisition module 11 is configured to acquire a plurality of images captured by vehicle-mounted cameras deployed at different positions on a vehicle of the vehicle, and perform internal and external reference calibration on each vehicle-mounted camera according to the images; the matching module 12 is used for matching the image shot by each vehicle-mounted camera with a preset 3D model to construct a plurality of initial 3D models; the calculation module 13 is configured to calculate a pixel coordinate correspondence table between each initial 3D model and an image captured by the corresponding vehicle-mounted camera according to the calibrated internal and external parameters of each vehicle-mounted camera; a synthesis module 14, configured to perform texture binding on each initial 3D model based on the pixel coordinate correspondence table; and synthesizing the plurality of bound initial 3D models to obtain the vehicle-mounted 3D panoramic all-around model.
Further, the obtaining module 11 includes: the calibration unit is used for carrying out internal reference calibration on each vehicle-mounted camera; the determining unit is used for determining the direction of a calibration plate which is used for performing external reference calibration by each vehicle-mounted camera in the vehicle, and measuring the distance from the calibration plate to the center of the vehicle body of the vehicle; and the calculation unit is used for calculating an external parameter matrix of each vehicle-mounted camera through an external parameter estimation method based on the direction of the calibration plate in the vehicle and the distance from the calibration plate to the center of the vehicle body of the vehicle.
Example 3
Referring to fig. 6, in a third aspect of the present invention, there is provided an electronic apparatus comprising: one or more processors; storage means for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to carry out the method of the invention in the first aspect.
The electronic device 500 may include a processing means (e.g., central processing unit, graphics processor, etc.) 501 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM) 502 or a program loaded from a storage means 508 into a Random Access Memory (RAM) 503. In the RAM503, various programs and data necessary for the operation of the electronic apparatus 500 are also stored. The processing device 501, the ROM502, and the RAM503 are connected to each other through a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
The following devices may be connected to the I/O interface 505 in general: input devices 506 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 507 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; a storage device 508 including, for example, a hard disk; and a communication device 509. The communication means 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. While fig. 6 illustrates an electronic device 500 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided. Each block shown in fig. 6 may represent one device or may represent multiple devices as desired.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication means 509, or installed from the storage means 508, or installed from the ROM 502. The computer program, when executed by the processing device 501, performs the above-described functions defined in the methods of embodiments of the present disclosure. It should be noted that the computer readable medium described in the embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In embodiments of the disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In embodiments of the present disclosure, however, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more computer programs which, when executed by the electronic device, cause the electronic device to:
computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C + +, python, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and should not be taken as limiting the scope of the present invention, which is intended to cover any modifications, equivalents, improvements, etc. within the spirit and scope of the present invention.
Claims (10)
1. A3D panoramic all-round looking model construction method for a vehicle is characterized by comprising the following steps:
acquiring a plurality of images shot by vehicle-mounted cameras arranged at different positions on a vehicle of the vehicle, and calibrating internal and external parameters of each vehicle-mounted camera according to the images;
matching the image shot by each vehicle-mounted camera with a preset 3D model to construct a plurality of initial 3D models;
calculating a pixel coordinate corresponding relation table of each initial 3D model and an image shot by the corresponding vehicle-mounted camera according to the calibrated internal and external parameters of each vehicle-mounted camera;
performing texture binding on each initial 3D model based on the pixel coordinate corresponding relation table; and synthesizing the plurality of bound initial 3D models to obtain the vehicle-mounted 3D panoramic all-around model.
2. The method for constructing a 3D panoramic all-around model of a vehicle according to claim 1, wherein the obtaining a plurality of images taken by vehicle-mounted cameras deployed at different positions on the vehicle and performing internal and external reference calibration on each vehicle-mounted camera according to the images comprises:
carrying out internal reference calibration on each vehicle-mounted camera;
determining the direction of a calibration plate which is subjected to external parameter calibration by each vehicle-mounted camera in a vehicle, and measuring the distance from the calibration plate to the center of the vehicle body of the vehicle;
and calculating an external parameter matrix of each vehicle-mounted camera by an external parameter estimation method based on the direction of the calibration plate in the vehicle and the distance from the calibration plate to the center of the body of the vehicle.
3. The vehicle 3D panoramic looking-around model building method according to claim 2, wherein the calculating the external parameter matrix of each vehicle-mounted camera through an external parameter estimation method based on the direction of the calibration plate in the own vehicle and the distance from the calibration plate to the center of the body of the own vehicle comprises:
determining coordinates of the corner points of the calibration plate in an image shot by the vehicle-mounted camera;
and calculating an external parameter matrix of each vehicle-mounted camera according to the calibrated internal parameters, coordinates of the angular points of the calibration plate in an image shot by the vehicle-mounted camera, the direction of the calibration plate in the vehicle and the distance from the calibration plate to the center of the vehicle body of the vehicle.
4. The method for constructing the 3D panoramic all-around view model of the vehicle according to claim 1, wherein the step of calculating the pixel coordinate corresponding relation table of each initial 3D model and the image shot by the corresponding vehicle-mounted camera according to the calibrated internal and external parameters of each vehicle-mounted camera comprises the following steps:
reading the vertex coordinates of each initial 3D model;
calculating the coordinates of pixels in the visual angle image corresponding to each vehicle-mounted camera according to the calibrated internal and external parameters of each vehicle-mounted camera;
and constructing a corresponding relation table according to the vertex coordinates of each initial 3D model and the coordinates of the pixels in the corresponding view angle image.
5. The method for constructing the 3D panoramic all-around model of the vehicle according to claim 4, wherein the method for calculating the coordinates of the pixels in the view angle image corresponding to each vehicle-mounted camera according to the calibrated internal and external parameters of each vehicle-mounted camera comprises the following steps:
wherein (u, v) represents pixel coordinates in the angle-of-view image,
for each of the onboard cameras' internal reference matrix,
for each vehicle camera's extrinsic matrix, (x, y, z) are the vertex coordinates of the initial 3D model.
6. The vehicle 3D panoramic all-around model building method according to any one of claims 1 to 5, wherein the texture binding each initial 3D model based on the pixel coordinate correspondence table comprises:
based on the pixel coordinate corresponding relation table, searching a pixel value corresponding to each vertex coordinate;
and traversing each pixel of the image shot by each vehicle-mounted camera to obtain pixel values corresponding to all vertexes of each initial 3D model.
7. The utility model provides a vehicle 3D panorama look around model construction equipment which characterized in that includes:
the system comprises an acquisition module, a parameter calibration module and a parameter calibration module, wherein the acquisition module is used for acquiring a plurality of images shot by vehicle-mounted cameras arranged at different positions on a vehicle of the user and calibrating internal and external parameters of each vehicle-mounted camera according to the images;
the matching module is used for matching the image shot by each vehicle-mounted camera with a preset 3D model and constructing a plurality of initial 3D models;
the calculation module is used for calculating a pixel coordinate corresponding relation table of each initial 3D model and an image shot by the corresponding vehicle-mounted camera according to the calibrated internal and external parameters of each vehicle-mounted camera;
the synthesis module is used for performing texture binding on each initial 3D model based on the pixel coordinate corresponding relation table; and synthesizing the plurality of bound initial 3D models to obtain the vehicle-mounted 3D panoramic all-around model.
8. The vehicle 3D panoramic looking-around model building device according to claim 7, wherein the obtaining module comprises:
the calibration unit is used for carrying out internal reference calibration on each vehicle-mounted camera;
the determining unit is used for determining the direction of a calibration plate which is used for performing external reference calibration by each vehicle-mounted camera in the vehicle, and measuring the distance from the calibration plate to the center of the vehicle body of the vehicle;
and the calculation unit is used for calculating an external parameter matrix of each vehicle-mounted camera through an external parameter estimation method based on the direction of the calibration plate in the vehicle and the distance from the calibration plate to the center of the body of the vehicle.
9. An electronic device, comprising: one or more processors; storage means for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the vehicle 3D panoramic all around model construction method as claimed in any one of claims 1 to 6.
10. A computer-readable medium, on which a computer program is stored, wherein the computer program, when being executed by a processor, implements the vehicle 3D panoramic view model construction method according to any one of claims 1 to 6.
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