Dynamic look-around splicing method and system based on tire pressure monitoring

Abstract

The invention provides a dynamic look-around splicing method and system based on tire pressure monitoring, and the method comprises the steps: carrying out the quantitative processing of a tire pressure value according to the preset vehicle information of a target vehicle, so as to obtain a tire pressure data segment array of the target vehicle; the tire pressure data segment array comprises a plurality of tire pressure data segments; according to each tire pressure data segment, respectively constructing a mapping relation table of each tire pressure data segment to obtain a total mapping relation table; performing matching search according to the real-time tire pressure data of the target vehicle and the total mapping relation table to obtain a target mapping relation table of the real-time tire pressure data; and performing all-round stitching of the target vehicle according to the target mapping relation table. By quantifying the tire pressure value in the tire pressure monitoring system, the calculation amount of the Map mapping lookup table caused by frequent change of the tire pressure value is reduced, and the calculation amount of subsequently establishing the tire pressure value and the Map mapping lookup table is also reduced.

Description

Technical Field

[0001] The present application belongs to the field of image processing technology, and relates to a dynamic surround view stitching method based on tire pressure monitoring, and in particular to a dynamic surround view stitching method and system based on tire pressure monitoring. Background Art

[0002] With the rapid development of artificial intelligence technology, the intelligent development of automobiles is also getting faster and faster. With the maturity of L1 assisted driving, L2 advanced assisted driving is also booming, especially advanced assisted driving based on pure visual perception is becoming more and more popular in the industry.

[0003] In automatic parking perception, some vehicle control planning strategies are often made based on the surround view stitching map. When doing surround view stitching, the internal and external parameters of the surround view camera are needed, especially the calibration of external parameters. At present, most traditional external parameter calibration methods are based on the special chessboard grid in the calibration plant to perform static camera external parameter calibration; in addition, in some cases, the calibration of external parameters is semi-dynamic and needs to be dynamically calibrated based on the lane lines on the road. In this case, the external parameter calibration requires the car to be driven to a designated straight road with lane lines, and there are certain requirements for the vehicle speed during the external parameter calibration.

[0004] The above two traditional external parameter calibration methods are easily affected by the tire pressure of the car during the external parameter calibration. When calibrating the camera external parameters, the external parameters at the moment of calibration are only suitable for the tire pressure value at that moment. When the tire pressure changes, the picture taken by the camera will be offset. This offset will cause the camera external parameters to change, thereby affecting the surround view stitching effect. Summary of the invention

[0005] The present application provides a dynamic surround view stitching method and system based on tire pressure monitoring, which is used to solve the problem that the tire pressure value in the traditional external parameter calibration method changes frequently and the change amplitude varies, causing the picture taken by the camera to shift, causing the camera external parameters to change, thereby affecting the surround view stitching effect.

[0006] In a first aspect, the present application provides a dynamic surround view stitching method based on tire pressure monitoring, the method comprising: performing tire pressure value quantization processing according to preset vehicle information of a target vehicle to obtain a tire pressure data segment array of the target vehicle; the tire pressure data segment array comprises a plurality of tire pressure data segments; constructing a mapping relationship table for each tire pressure data segment according to each tire pressure data segment to obtain a total mapping relationship table; performing a matching search according to the real-time tire pressure data of the target vehicle and the total mapping relationship table to obtain a target mapping relationship table for the real-time tire pressure data; and performing surround view stitching of the target vehicle according to the target mapping relationship table.

[0007] In an implementation of the first aspect, the preset vehicle information includes images of each perspective and corresponding tire pressure data; quantizing the tire pressure values ​​according to the preset vehicle information of the target vehicle to obtain a segmented array of tire pressure data of the target vehicle includes: pressurizing and / or decompressing the images of each perspective and the corresponding tire pressure data to obtain an image offset relationship; quantizing the tire pressure values ​​according to the image offset relationship to obtain a segmented array of tire pressure data of the target vehicle.

[0008] In an implementation of the first aspect, pressurization and / or decompression processing is performed according to the images of each perspective and the corresponding tire pressure data to obtain the image offset relationship, including: calibrating the target vehicle through grid calibration according to the images of each perspective to obtain the first coordinate data of the target vehicle; the first coordinate data includes the coordinates of the calibrated corner points of each perspective; pressurization and / or decompression processing is performed with a preset step according to the tire pressure data to obtain the second coordinate data of the target vehicle; the second coordinate data includes the coordinates of the calibrated corner points of each perspective after the pressurization and / or decompression processing; Euclidean distance calculation is performed according to the first coordinate data and the second coordinate data to obtain a first Euclidean distance group; the first Euclidean distance group includes the Euclidean distances of the calibrated corner points of each perspective before and after the pressurization and / or decompression processing; iterative processing is performed in sequence to obtain N groups of Euclidean distance groups; wherein N>=1 and is an integer; average value calculation is performed on the N groups of Euclidean distance groups to obtain an average value; and the image offset relationship is obtained according to the average value.

[0009] In an implementation of the first aspect, tire pressure values ​​are quantized according to the image offset relationship to obtain a segmented array of tire pressure data of the target vehicle, including: pixel conversion is performed according to the image offset relationship to obtain a tire pressure error; and tire pressure error and a preset tire pressure range are used to obtain a segmented array of tire pressure data of the target vehicle.

[0010] In an implementation of the first aspect, a mapping relationship table for each of the tire pressure data segments is constructed respectively according to each of the tire pressure data segments to obtain a total mapping relationship table, including: obtaining target tire pressure data for each of the tire pressure data segments respectively according to each of the tire pressure data segments; obtaining images of corresponding perspectives respectively according to the target tire pressure data of each of the tire pressure data segments; and constructing a mapping relationship table for each of the tire pressure data segments according to the images of each of the perspectives to obtain a total mapping relationship table.

[0011] In an implementation of the first aspect, a mapping relationship table for each tire pressure data segment is constructed according to the images of each perspective respectively to obtain a total mapping relationship table, including: performing distortion correction processing according to the images of each perspective to obtain correction data of each perspective; the correction data includes a correction image and a distortion correction lookup table; performing perspective transformation processing according to the correction image of each perspective and the corresponding calibration corner points to obtain perspective transformation data of each perspective; the perspective transformation data includes a perspective transformation matrix and a corresponding bird's-eye view image; performing fusion processing according to the bird's-eye view image of each perspective to obtain a fusion matrix; performing fusion processing according to the distortion correction lookup table of each perspective, the perspective transformation matrix of each perspective and the fusion matrix to obtain a mapping relationship table corresponding to the current tire pressure data segment; and using the mapping relationship table corresponding to each tire pressure data segment as the total mapping relationship table.

[0012] In an implementation of the first aspect, performing fusion processing according to the distortion correction lookup table of each viewing angle, the perspective transformation matrix of each viewing angle, and the fusion matrix to obtain a mapping relationship table corresponding to the current tire pressure data segment includes: performing fusion processing according to the distortion correction lookup table of each viewing angle and the perspective transformation matrix of each viewing angle to obtain fusion data of each viewing angle; the fusion data includes a fusion lookup table and a viewing angle area; the viewing angle area includes a fusion area and a non-fusion area; establishing fusion parameters according to the fusion lookup table of each viewing angle, the fusion area of ​​each viewing angle, and the fusion matrix to obtain the mapping relationship table corresponding to each group of tire pressure data; wherein the fusion parameters are:

[0013]

[0014] Among them, dist represents the Euclidean distance, px is the pixel coordinate in the fusion area of ​​each viewing area, c1 and c2 represent the geometric center coordinates of two adjacent viewing areas, and s represents the fusion area of ​​all viewing areas.

[0015] In an implementation of the first aspect, matching and searching are performed based on the real-time tire pressure data of the target vehicle and the total mapping relationship table to obtain a target mapping relationship table for the real-time tire pressure data, including: obtaining the real-time tire pressure data of the target vehicle; obtaining the tire pressure data segment to which the real-time tire pressure data belongs based on the real-time tire pressure data and the tire pressure data segment array; matching and searching are performed based on the tire pressure data segment to which the real-time tire pressure data belongs and the total mapping relationship table to obtain a mapping relationship table corresponding to the tire pressure data segment to which the real-time tire pressure data belongs, and using the mapping relationship table as the target mapping relationship table for the real-time tire pressure data.

[0016] In an implementation of the first aspect, performing surround view stitching of the target vehicle according to the target mapping relationship table includes: acquiring images of corresponding perspectives according to the real-time tire pressure data; acquiring perspective areas of each perspective respectively according to the images of each perspective; the perspective areas include fusion areas and non-fusion areas; performing fusion processing on the fusion areas of each adjacent perspective according to the target mapping relationship table to obtain pixel information of the fusion areas of each adjacent perspective; performing calculations according to the target mapping relationship table and the non-fusion areas of each perspective to obtain pixel information of the non-fusion areas of each perspective; performing surround view stitching according to the fusion areas of each adjacent perspective and the pixel information of the non-fusion areas of each perspective to obtain a target surround view stitching map.

[0017] In a second aspect, the present application provides a dynamic surround view stitching system based on tire pressure monitoring, the system comprising: a tire pressure value quantification processing module, used to perform tire pressure value quantification processing according to preset vehicle information of a target vehicle, so as to obtain a tire pressure data segment array of the target vehicle; the tire pressure data segment array comprises a plurality of tire pressure data segments; a mapping relationship table construction module, used to construct a mapping relationship table for each tire pressure data segment according to each tire pressure data segment, so as to obtain a total mapping relationship table; a target mapping relationship table acquisition module, used to perform matching and searching according to the real-time tire pressure data of the target vehicle and the total mapping relationship table, so as to obtain a target mapping relationship table of the real-time tire pressure data; a surround view stitching module, used to perform surround view stitching of the target vehicle according to the target mapping relationship table.

[0018] In a third aspect, the present application provides an electronic device, comprising: a memory and a processor; wherein the memory is used to store a computer program; and the processor is used to execute the computer program stored in the memory, so that the electronic device executes the dynamic surround view stitching method based on tire pressure monitoring as described above.

[0019] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by an electronic device, implements the above-mentioned dynamic surround view stitching method based on tire pressure monitoring.

[0020] As described above, the dynamic surround view stitching method and system based on tire pressure monitoring described in this application have the following beneficial effects:

[0021] The present application performs quantification processing of tire pressure values ​​according to preset vehicle information of the target vehicle to obtain a segmented array of tire pressure data of the target vehicle; the segmented array of tire pressure data includes a plurality of tire pressure data segments; a mapping relationship table of each tire pressure data segment is constructed according to each tire pressure data segment to obtain a total mapping relationship table; a matching search is performed according to the real-time tire pressure data of the target vehicle and the total mapping relationship table to obtain a target mapping relationship table of the real-time tire pressure data; and a surround view splicing of the target vehicle is performed according to the target mapping relationship table. The present application reduces the amount of calculation of the Map lookup table caused by frequent changes in tire pressure values ​​by quantifying the tire pressure values ​​in the tire pressure monitoring system, and also reduces the amount of calculation for subsequently establishing a mapping relationship between tire pressure values ​​and Maps.

[0022] The present application obtains a mapping relationship table by performing calculations based on the tire pressure value array, and establishes the entire surround-view stitching process of obtaining the BEV bird's-eye view from distortion correction, perspective transformation, and alpha fusion as a total lookup table Map, and maps the pixels at specified positions in the four original images to the BEV bird's-eye view, thereby reducing the calculations of distortion correction, perspective transformation, and alpha fusion, and does not rely on the high computing power brought by the GPU. The surround-view stitching runs fast and is easy to port to mobile terminals.

[0023] The present application obtains a mapping relationship table by performing calculations based on the tire pressure value array, and establishes the entire surround-view stitching process of the BEV bird's-eye view obtained from distortion correction, perspective transformation, and alpha fusion as a total lookup table Map, directly indexes the pixels in the original image to the BEV bird's-eye view, and then establishes a mapping relationship between the tire pressure values ​​directly from the automobile tire pressure monitoring system and the total lookup table Map, thereby realizing a dynamic surround-view stitching algorithm based on tire pressure monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1A Shown is a schematic diagram of an application scenario of the dynamic surround view stitching method based on tire pressure monitoring described in this application.

[0025] Figure 1B Shown are structural diagrams of the client-cloud interaction scenarios in these implementations.

[0026] Figure 2 Shown is a flow chart of the dynamic surround view stitching method based on tire pressure monitoring described in an embodiment of the present application.

[0027] Figure 3 Shown is a flow chart of a dynamic surround view stitching method based on tire pressure monitoring according to another embodiment of the present application.

[0028] Figure 4 Shown is a schematic diagram of a bird's-eye view of a target vehicle described in an embodiment of the present application.

[0029] Figure 5 Shown is a schematic diagram of the surround stitching process described in an embodiment of the present application.

[0030] Figure 6 Shown is a structural schematic diagram of a dynamic surround view stitching system based on tire pressure monitoring described in an embodiment of the present application.

[0031] Figure 7 Shown is a schematic diagram of the structure of an electronic device described in an embodiment of the present application.

[0032] Component number description

[0033] 1 Dynamic surround view stitching device based on tire pressure monitoring

[0034] 11 Vehicle information collection equipment

[0035] 12 Local Processor

[0036] 13 Display Terminal

[0037] 2-end-cloud interactive system

[0038] 20 Terminal

[0039] 21 Cloud Server

[0040] 3 Dynamic surround view stitching system based on tire pressure monitoring

[0041] 31 Tire pressure value quantification processing module

[0042] 32 Mapping relationship table building module

[0043] 33 Target mapping relationship table acquisition module

[0044] 34 Surround view splicing module

[0045] 4 Electronic devices

[0046] 41 Processor / Processing Unit

[0047] 42 Memory

[0048] 421 RAM

[0049] 422 Cache memory

[0050] 423 Storage System

[0051] 424 Programs / Utilities

[0052] 4241 Program Module

[0053] 43 Bus

[0054] 44 Input / Output Interfaces

[0055] 45 Network Adapter

[0056] Steps S1 to S4 DETAILED DESCRIPTION

[0057] The following describes the embodiments of the present application through specific examples, and those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0058] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present application, and thus the drawings only show components related to the present application rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed at will, and the component layout may also be more complicated.

[0059] It should be noted that in the embodiments of the present application, words such as "exemplary" or "for example" represent examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0060] The traditional external parameter calibration method is not only easily affected by the tire pressure of the car during the external parameter calibration, but also when calibrating the camera external parameters, the external parameters at the moment of calibration are only suitable for the tire pressure value at that moment. When the tire pressure changes, the image captured by the camera will be offset. This offset will cause the camera external parameters to change, thereby affecting the surround stitching effect. In addition, in surround stitching, the fisheye camera has a wide field of view and a strong sense of spatial stereo, but the imaging distortion is serious. Generally, it is necessary to perform distortion correction on the fisheye image, and then perform perspective transformation based on the correction image, and then obtain the surround stitching image based on Alpha fusion. In the middle, it undergoes multiple pixel position transformations and pixel value weighted processing. The stitching algorithm is complex and runs slowly, which is not conducive to porting to the board end for operation.

[0061] The following embodiments of the present application provide a dynamic surround view stitching method and system based on tire pressure monitoring, which solves the problem that the tire pressure values ​​in the traditional external parameter calibration method change frequently and the change amplitude varies, causing the picture taken by the camera to shift, causing the camera external parameters to change, thereby affecting the surround view stitching effect.

[0062] Figure 1A The figure shows an application scenario of the dynamic surround view stitching method based on tire pressure monitoring described in the present application. The dynamic surround view stitching device 1 based on tire pressure monitoring can be used to implement the dynamic surround view stitching method based on tire pressure monitoring provided in the embodiment of the present application, but the application scenario of the dynamic surround view stitching method based on tire pressure monitoring provided in the embodiment of the present application is not limited to Figure 1A The dynamic surround view stitching device 1 based on tire pressure monitoring is shown. Figure 1A As shown, the dynamic surround view stitching device 1 based on tire pressure monitoring includes a vehicle information collection device 11, a local processor 12 and a display terminal 13. The dynamic surround view stitching method based on tire pressure monitoring provided in the embodiment of the present application can be applied to the local processor 12.

[0063] in, Figure 1A The local processor 12 in the embodiment may be a local processor or a local processor cluster composed of multiple local processors or a cloud computing center, etc., which is not limited to the specifics herein. Figure 1A Only one vehicle information collection device 11, one local processor 12 and one display terminal 13 are shown, but it should be understood that Figure 1A The examples are only used to understand the present solution, and the specific numbers of local processors 12 and display terminals 13 should be flexibly determined based on actual conditions.

[0064] In some other implementations, the dynamic surround view stitching device 1 based on tire pressure monitoring may not include the display terminal 13, but only include a local processor 12 with a display function and a driving information collection device 11. The dynamic surround view stitching method based on tire pressure monitoring provided in the embodiment of the present application can be applied to the local processor 12. The local processor 12 with a display function may include a tablet computer, a laptop computer, a PDA, a mobile phone, a personal computer (Personal Computer, referred to as PC) and a voice interaction device, and may also be a monitoring device, a face recognition device, etc., which is not limited here.

[0065] In still other implementations, the dynamic surround view stitching method based on tire pressure monitoring described in this application can be applied to end-cloud interaction scenarios. Figure 1B The following is a schematic diagram of the structure of the client-cloud interaction scenario in these implementations. Figure 1B As shown, the terminal-cloud interaction system 2 includes a terminal 20 and a cloud server 21. The terminal 20 and the cloud server 21 can communicate with each other, and the communication method is not limited to wired or wireless.

[0066] Among them, the terminal 20 can be mobile or fixed, for example, the terminal 20 can be a wireless terminal or a wired terminal. The wireless terminal can refer to a device with wireless transceiver function, which can be deployed indoors, outdoors and in industrial workshops. The terminal 20 can be a vehicle-mounted system, a mobile phone (Mobile Phone), a tablet computer (Pad), a laptop computer, etc., which is not limited here. The cloud server 21 can include one or more servers, or one or more processing nodes, or one or more virtual machines running on the server. The cloud server 21 can also be called a server cluster, a management platform, a data processing center, etc., which is not limited in the embodiments of the present application.

[0067] The technical solutions in the embodiments of the present application will be described in detail below in conjunction with the drawings in the embodiments of the present application.

[0068] The following embodiments of the present application provide a dynamic surround view stitching method based on tire pressure monitoring, which can be performed by Figure 1A The local processor 12 shown or Figure 1B It is implemented by the cloud server 21 shown. Figure 2 The figure shows a flow chart of the dynamic surround view stitching method based on tire pressure monitoring described in the embodiment of the present application. Figure 2 As shown, this embodiment provides a dynamic surround view stitching method based on tire pressure monitoring, and the dynamic surround view stitching method based on tire pressure monitoring includes the following steps S1 to S4.

[0069] Step S1, performing tire pressure value quantization processing according to preset vehicle information of a target vehicle to obtain a tire pressure data segment array of the target vehicle. The tire pressure data segment array includes a plurality of tire pressure data segments; the preset vehicle information includes images of each viewing angle and corresponding tire pressure data, and the images of each viewing angle include images of the front, rear, left and right four viewing angles of the target vehicle.

[0070] Specifically, the present application performs quantization processing on tire pressure values ​​according to preset vehicle information to obtain a segmented array of tire pressure data, thereby reducing the amount of calculation for subsequently establishing a reasonable mapping relationship.

[0071] In some implementations, the present application obtains original images (fisheye images) of the front, rear, left, and right azimuth perspectives of the target vehicle through a surround-view camera (eg, a fisheye camera).

[0072] The tire pressure data segment array is within the normal tire pressure range of a car, for example, the normal tire pressure of a small car is within 250 kpa (2.5 bar).

[0073] In one embodiment of the present application, performing tire pressure value quantization processing according to preset vehicle information of a target vehicle to obtain a segmented array of tire pressure data of the target vehicle includes the following steps S11 to S12.

[0074] Step S11: performing pressurization and / or decompression processing according to the images of each viewing angle and the corresponding tire pressure data to obtain an image offset relationship.

[0075] Step S12: performing tire pressure value quantization processing according to the image offset relationship to obtain a segmented array of tire pressure data of the target vehicle.

[0076] In one embodiment of the present application, performing pressurization and / or decompression processing according to the images of each viewing angle and the corresponding tire pressure data to obtain the image offset relationship includes the following steps S111 to S116.

[0077] Step S111, calibrating the target vehicle through grid calibration according to the images of each viewing angle to obtain first coordinate data of the target vehicle; the first coordinate data includes the coordinates of the calibration corner points of each viewing angle.

[0078] Step S112, pressurizing and / or depressurizing the tire according to the tire pressure data with a preset step to obtain second coordinate data of the target vehicle; the second coordinate data includes the coordinates of the calibrated corner points of each viewing angle after the pressurization and / or depressurization processing.

[0079] Step S113, performing Euclidean distance calculation according to the first coordinate data and the second coordinate data to obtain a first Euclidean distance group; the first Euclidean distance group includes the Euclidean distances of the calibrated corner points of each viewing angle before and after the pressurization and / or decompression treatment.

[0080] Step S114, iteratively process in sequence to obtain N groups of Euclidean distance groups; wherein N>=1 and is an integer.

[0081] Step S115: Calculate the average value of the N groups of Euclidean distances to obtain an average value.

[0082] Step S116: Acquire the image offset relationship according to the average value.

[0083] In one embodiment of the present application, performing tire pressure value quantization processing according to the image offset relationship to obtain a segmented array of tire pressure data of the target vehicle includes the following steps S121 to S122.

[0084] Step S121: Perform pixel conversion according to the image offset relationship to obtain tire pressure error.

[0085] Step S122: acquiring a segmented array of tire pressure data of the target vehicle according to the tire pressure error and a preset tire pressure range, wherein the preset tire pressure range is a normal tire pressure range of 150 kpa-250 kpa.

[0086] In some implementations, the present application is carried out by covering a target vehicle with a normal tire pressure of 250kpa with a calibration cloth similar to a chessboard, and obtaining fisheye images of the front, rear, left and right directions of the vehicle according to the fisheye camera set on the target vehicle, finding the corner point closest to the fisheye camera in the four fisheye images of the front, rear, left and right, and recording the image coordinates of the corresponding four points; then, according to the alarm threshold of the vehicle tire pressure monitoring system and the normal tire pressure range, the vehicle tire is depressurized or pressurized, and the corresponding nearest corner point in the four fisheye images is re-obtained, and multiple groups of the above operations are repeated; finally, according to the calculated multiple groups of image offset errors, the tire pressure value is quantized to obtain a quantized tire pressure value array TP, thereby reducing the subsequent mapping relationship calculation amount.

[0087] Since the tire pressure values ​​in the tire pressure monitoring system change frequently and the magnitude of the changes varies, the present application establishes an offset relationship between the tire pressure values ​​in the tire pressure monitoring system and the surround-view camera image, and quantifies the tire pressure values ​​based on this offset relationship, thereby reducing the amount of calculation for subsequently establishing a reasonable mapping relationship.

[0088] Step S2: construct mapping relationship tables for each tire pressure data segment according to each tire pressure data segment to obtain a total mapping relationship table. The total mapping relationship table includes the mapping relationship tables for each tire pressure data segment.

[0089] Specifically, the present application constructs a mapping relationship table for each tire pressure data segment respectively, and uses the mapping relationship table for each tire pressure data segment as a total mapping relationship table to facilitate the subsequent surround view stitching process.

[0090] In one embodiment of the present application, constructing a mapping relationship table for each tire pressure data segment according to each tire pressure data segment to obtain a total mapping relationship table includes the following steps S21 to S23.

[0091] Step S21, respectively obtaining target tire pressure data of each tire pressure data segment according to each tire pressure data segment.

[0092] Step S22: acquiring images of corresponding viewing angles according to the target tire pressure data of each tire pressure data segment.

[0093] Step S23: constructing mapping relationship tables of the tire pressure data segments according to the images of the respective viewing angles to obtain a total mapping relationship table.

[0094] Specifically, the present application constructs a mapping relationship table corresponding to the tire pressure data segment according to the target tire pressure data of each tire pressure data segment. For example, the tire pressure data segment array is [[150,160], [160,170], [170,180], [180,190], [190,200]], and the target tire pressure data corresponding to these five tire pressure data segments are [155, 165, 175, 185, 195]. Then, according to these target tire pressure data, the corresponding images of each perspective are obtained respectively. For example, when the target tire pressure data is 155, when the tire pressure data of the target vehicle is 155, the images of the four azimuth perspectives of front, back, left, and right are obtained, so as to construct a corresponding mapping relationship table according to the images of these four azimuth perspectives, and use this mapping relationship table as the mapping relationship table of this tire pressure data segment, that is, when the tire pressure data of the target vehicle is in this tire pressure data segment, this mapping relationship table is used for the surround stitching of the target vehicle.

[0095] It should be noted that for each tire pressure data segment, the target tire pressure data is the average value of the tire pressure data in the tire pressure data segment as the optimal option, and the error during surround stitching is minimal. For example, for the tire pressure data segment [150,160], the target tire pressure data is 155. When the real-time tire pressure data of the target vehicle is 151, the error during surround stitching is relatively small. If the target tire pressure data is 159 and the real-time tire pressure data of the target vehicle is 151, the error during surround stitching is relatively large. When the target tire pressure data is other tire pressure data in the tire pressure data segment, the error during surround stitching is also within the allowable error range, and this application is not limited to this.

[0096] In one embodiment of the present application, constructing a mapping relationship table for each of the tire pressure data segments according to the images of each of the viewing angles to obtain a total mapping relationship table includes the following steps S231 to S235.

[0097] Step S231: performing distortion correction processing on the images at each viewing angle to obtain correction data at each viewing angle; the correction data includes a correction image and a distortion correction lookup table.

[0098] Step S232: Perform perspective transformation processing according to the corrected image of each viewing angle and the corresponding calibrated corner points to obtain perspective transformation data of each viewing angle; the perspective transformation data includes a perspective transformation matrix and a corresponding bird's-eye view image.

[0099] Step S233: performing fusion processing on the bird's-eye view images of each viewing angle to obtain a fusion matrix.

[0100] Step S234: performing fusion processing according to the distortion correction lookup table of each viewing angle, the perspective transformation matrix of each viewing angle and the fusion matrix to obtain a mapping relationship table corresponding to the current tire pressure data segment.

[0101] Step S235: taking the mapping relationship table corresponding to each tire pressure data segment as the total mapping relationship table.

[0102] In one embodiment of the present application, a fusion process is performed based on the distortion correction lookup table of each viewing angle, the perspective transformation matrix of each viewing angle and the fusion matrix to obtain a mapping relationship table corresponding to the current tire pressure data segment, including the following steps S2341 to S2342.

[0103] Step S2341, performing fusion processing according to the distortion correction lookup table of each viewing angle and the perspective transformation matrix of each viewing angle to obtain fusion data of each viewing angle; the fusion data includes the fusion lookup table and the viewing angle area; the viewing angle area includes a fusion area and a non-fusion area.

[0104] Step S2342: Establish fusion parameters according to the fusion lookup table of each viewing angle, the fusion area of ​​each viewing angle and the fusion matrix to obtain the mapping relationship table corresponding to each set of tire pressure data; wherein the fusion parameters are:

[0105]

[0106] Among them, dist represents the Euclidean distance, dist(px,c1) represents the Euclidean distance of (px,c1), dist(px,c2) represents the Euclidean distance of (px,c2), px is the pixel coordinate in the fusion area of ​​each viewing area, c1 and c2 represent the geometric center coordinates of two adjacent viewing areas, s represents the fusion area of ​​all viewing areas, and s includes (s1,s2,s3,s4).

[0107] In some implementations, the present application first sets several groups of tire pressure data based on the tire pressure value array (the value of each group of tire pressure data is within the range of the tire pressure value array), and obtains the fisheye image corresponding to each group of tire pressure data through the fisheye camera, performs distortion correction on the fisheye image, calculates the distortion correction lookup table map1 from the original image to the corrected image, and then performs perspective transformation processing based on the one-to-one correspondence between the coordinate points of the calibrated corner points around the vehicle under the bird's-eye view and the pixel coordinate points in the distortion correction image, and obtains the corresponding perspective transformation matrix H, which converts the original camera perspective into a bird's-eye view. Secondly, the present application performs the above-mentioned bird's-eye view conversion operation on the images obtained by the four surround-view cameras in the front, back, left and right, and obtains four bird's-eye view images (i.e., the bird's-eye view images corresponding to the images obtained by the four surround-view cameras in the front, back, left and right of the target vehicle), and performs Alpha fusion on the four bird's-eye view images according to the parameter settings of the surround-view stitching to obtain the final surround-view stitching image, and calculates the Alpha fusion matrix B at the same time. Finally, according to the three variables map1, H, and B, the mapping relationship lookup table Map from the original fisheye image directly to the surround view spliced ​​image is calculated.

[0108] Step S3: performing a match search based on the real-time tire pressure data of the target vehicle and the total mapping relationship table to obtain a target mapping relationship table of the real-time tire pressure data.

[0109] Specifically, the present application is based on the real-time tire pressure data of the target vehicle, by searching in the tire pressure data segment array which tire pressure data is located in, and obtaining a corresponding mapping relationship table based on the tire pressure data segment to which the real-time tire pressure data belongs, as the target mapping relationship table of the real-time tire pressure data.

[0110] In one embodiment of the present application, matching and searching are performed based on the real-time tire pressure data of the target vehicle and the total mapping relationship table to obtain the target mapping relationship table of the real-time tire pressure data, including the following steps S31 to S33.

[0111] Step S31, obtaining real-time tire pressure data of the target vehicle.

[0112] Step S32: acquiring the tire pressure data segment to which the real-time tire pressure data belongs according to the real-time tire pressure data and the tire pressure data segment array.

[0113] Step S33, matching and searching the tire pressure data segment to which the real-time tire pressure data belongs and the total mapping relationship table to obtain a mapping relationship table corresponding to the tire pressure data segment to which the real-time tire pressure data belongs, and using the mapping relationship table as the target mapping relationship table for the real-time tire pressure data.

[0114] Step S4: performing surround stitching of the target vehicle according to the target mapping relationship table.

[0115] In one embodiment of the present application, performing surround view stitching of the target vehicle according to the target mapping relationship table includes the following steps S41 to S45.

[0116] Step S41, acquiring images of corresponding viewing angles according to the real-time tire pressure data;

[0117] Step S42, obtaining a viewing area of ​​each viewing angle according to the image of each viewing angle; the viewing area includes a fusion area and a non-fusion area;

[0118] Step S43: performing fusion processing on the fusion areas of each adjacent perspective according to the target mapping relationship table to obtain pixel information of the fusion areas of each adjacent perspective;

[0119] Step S44: performing calculation according to the target mapping relationship table and the non-fused area of ​​each viewing angle to obtain pixel information of the non-fused area of ​​each viewing angle;

[0120] Step S45 , performing surround stitching according to the pixel information of the fused areas of each adjacent perspective and the non-fused areas of each perspective, so as to obtain a target surround stitching image.

[0121] The present application performs tire pressure value quantization processing through preset vehicle information of the target vehicle, obtains the tire pressure data segment array of the target vehicle, and constructs a mapping relationship table for each tire pressure data segment in the tire pressure data segment array. When the target vehicle performs surround stitching, the tire pressure data segment to which the real-time tire pressure data belongs is used, and the corresponding mapping relationship table is obtained, so that the surround stitching process is completed according to the obtained mapping relationship table.

[0122] The dynamic surround view stitching method based on tire pressure monitoring described in the embodiment of the present application establishes the entire surround view stitching process of obtaining the BEV bird's-eye view from distortion correction, perspective transformation, and alpha fusion as a lookup table Map, directly indexes the pixels in the original image to the BEV bird's-eye view, and then establishes a mapping relationship between the values ​​directly from the automobile tire pressure monitoring system and the lookup table Map, thereby realizing a dynamic surround view stitching algorithm based on tire pressure monitoring.

[0123] In some embodiments, Figure 3 Shown is a schematic flow chart of a dynamic surround view stitching method based on tire pressure monitoring according to another embodiment of the present application. Figure 4 The display is a bird's-eye view of the car described in the embodiment of the present application. Figure 3-4 As shown in FIG, the tire pressure monitoring system inputs a tire pressure value group TP, which contains the tire pressure values ​​of four tires. The corresponding surround stitching lookup table is Map, where i, j are the pixel index positions corresponding to the final surround stitching image BEV, and each index corresponds to an array [c, x1, y1, x2, y2, α] in Map, where c refers to which image block. Figure 4 As shown, when c=0\1\2\3, the corresponding Figure 4 The blank area image blocks in the four azimuth angles of view in the figure are shown in Figure 4. When c = 4\5\6\7, they correspond to the gray areas of the upper left corner, upper right corner, lower left corner and lower right corner of the figure respectively. (x1, y1) and (x2, y2) are the indices of the pixels in the corresponding input image respectively (such as Figure 3 As shown in , (x1, y1) corresponds to the index of the pixel in the input image img1, (x2, y2) corresponds to the index of the pixel in the input image img2), α is the coefficient of image Alpha fusion, where Figure 4 The blank space in the middle does not require image fusion, that is, a single front, back, left, and right image. Figure 3The gray area of ​​the single image corresponding to img in the image needs to be fused, where the upper left corner, upper right corner, lower left corner, and lower right corner correspond to the areas for Alpha fusion of the left view and the front view, the right view and the front view, the left view and the back view, and the right view and the back view, that is, s1, s2, s3, and s4. Figure 3 The image img1 in corresponds to one of the image areas s1, s2, s3, s4, and the image img2 corresponds to one of the image areas s1, s2, s3, s4.

[0124] In some implementations, the normal tire pressure range of a car is within 250kpa (2.5bar). The tire pressure warning thresholds of different cars are different. The tire pressure values ​​of most cars are 150kpa and 180kpa. This application selects the wider range of 150kpa. A tire pressure warning will appear below 150kpa, so this application sets the normal tire pressure to 150-250kpa (i.e., the preset tire pressure range), and the tire pressure selects a value within the range of 150-250kpa. The tire pressure value group TP output by the tire pressure monitoring system is obtained by quantifying the tire pressure values ​​between 150-250kpa. The specific steps of the quantization process of the tire pressure value group TP include the following steps S51 to S55.

[0125] Step S51: Spread a grid calibration cloth for static camera calibration around the vehicle to find corner points. Initialize the tire pressure values ​​of the four tires to 250 kpa, save a set of fisheye images as initialization images, select a corner point farthest from the camera in the front, rear, left, and right views of the initialization images, and record the coordinates of the farthest corner point on the image as (u0, v0), (u1, v1), (u2, v2), and (u3, v3) respectively. Among them, (u0, v0) is the farthest corner point of the front view, (u1, v1) is the farthest corner point of the rear view, (u2, v2) is the farthest corner point of the left view, and (u3, v3) is the farthest corner point of the right view.

[0126] Step S52: Increase or decrease the pressure on the four tires, with a step of 1 kPa. After increasing or decreasing the pressure, save the four corner points at this moment (1), and re-record their coordinates as (u0', v0'), (u1', v1'), (u2', v2'), (u3', v3'), and calculate the Euclidean distance dist between the corresponding corner points in sequence. Among them, (u0', v0') is the farthest corner point of the front view after increasing or decreasing the pressure, (u1', v1') is the farthest corner point of the rear view after increasing or decreasing the pressure, (u2', v2') is the farthest corner point of the left view after increasing or decreasing the pressure, and (u3', v3') is the farthest corner point of the right view after increasing or decreasing the pressure.

[0127] Step S53, assign (u0', v0'), (u1', v1'), (u2', v2'), (u3', v3') to (u0, v0), (u1, v1), (u2, v2), (u3, v3) in sequence.

[0128] Step S54, repeat steps S52-S53, calculate N groups of dist values, and calculate the average value of these N groups of dist values ​​as dm.

[0129] Step S55, based on steps S51 to S54, in order to quickly obtain the quantized results, this application takes N as 1000, and statistically obtains dm=1.6, and rounds dm down to 1, that is, a tire pressure change of 1kpa is approximately converted to a change of 1 pixel on the image. The actual distance corresponding to one pixel from the bird's-eye view is 2cm. The 2cm here refers to the downsampling ratio from the size of the field of view 2048x2048 to the size of the lookup table Map 1024x1024. The size of the general field of view is 1 pixel corresponding to 1cm, but downsampling will be selected according to the actual situation. The field of view selected in this application is about 20.48 meters, but if the lookup table is established with a size of 2048, there will be many redundant holes, which is not conducive to storage and reducing the amount of calculation. According to the actual situation, this application chooses a downsampling of 2 times. Then the error range allowed by this application is within 10cm. According to the experimental results, the surround stitching effect within this error range is within the normal range. If the error is larger, there will be a problem of splicing misalignment. Therefore, the present application directly quantifies the values ​​between 150-250 kPa as TPr=[[150,160],[160,170],[170,180],[180,190],[190,200],[200,210],[210,220],[220,230],[230,240],[240,250]], where the specific tire pressure values ​​corresponding to the 10 small segments are [155,165,175,185,195,205,215,225,235,245], which is the quantized tire pressure value group TPs.

[0130] In one implementation, the present application is based on the above-mentioned tire pressure value group TPs, and sets four tire pressure values ​​as the above-mentioned numerical values ​​at the same time, records 10 groups of front, back, left and right fisheye images imgs, and constructs a mapping relationship table of corresponding tire pressure value segments according to the fisheye images imgs.

[0131] Figure 5 The display is a schematic diagram of the surround stitching process described in the embodiment of the present application. Figure 5As shown, the surround view stitching process mainly includes a distortion correction process from a fisheye image to a correction image, a perspective transformation process from a correction image to a bird's-eye view image, and an Alpha fusion process from a bird's-eye view image to a surround view image. Specifically, firstly, the fisheye image is distorted and corrected to obtain a correction image and a distortion correction lookup table map1, the size of which is, for example, 4x2x960x1280, where 4 represents the dimension of the ID number array of the four cameras in the front, back, left and right, 2 represents the position index (x, y) dimension of the pixel at each position in the correction image in the original fisheye image, and 960x1280 represents the size of the correction image, which is consistent with the size of the original fisheye image; then, based on the correction image and the corner points on the calibration cloth around the car, the perspective transformation matrix H is calculated to obtain a size of 4x3x3, and four bird's-eye views under the corresponding front, back, left and right perspectives are obtained at the same time; finally, Alpha fusion is performed based on the four bird's-eye views to obtain the final surround stitching image and fusion matrix B, the size of which is 1x2048x2048, 1 represents the dimension of the Alpha fusion coefficient of each pixel, and 2048x2048 represents the surround field of view, that is, the size of the surround stitching image; in order to obtain the surround stitching lookup table Map, that is Figure 3 The process of the red arrow in the middle is realized by directly converting the fisheye image to the surround stitching image. The three matrices of map1, H and B need to be fused. The specific fusion steps are as follows: Steps S61 to S62.

[0132] Step S61, find the inverse matrix H-1 of the perspective transformation matrix H, expand each index (x0, y0) in the world coordinate system range under each bird's-eye view to [x0, y0, 1], and perform inner product processing with the three row vectors of H-1 to obtain [r1, r2, r3], x3 = r1 / r3, y3 = r2 / r3, and then find the corresponding position (x, y) of the pixel at the position (x3, y3) in the correction image in the original fisheye image, so as to establish a mapping relationship from the pixel position (x, y) in the original fisheye image to the pixel position (x0, y0) under the bird's-eye view, and finally realize the first stage of fusion processing, and fuse map1 and H together to obtain map2. Among them, the calculation formula of [r1, r2, r3] is as follows:

[0133]

[0134] Step S62: map2 in step S61 corresponds to four matrices of front, back, left, and right. The corresponding areas are as follows: Figure 4The four dotted areas in the figure correspond to the index positions of the pixels in the original image corresponding to the index positions from a bird's-eye view. The four gray areas are overlapping areas of vision and require Alpha fusion. The remaining blank areas can use the pixels from the perspective of this area (that is, the coefficient α of the image Alpha fusion is equal to 0). The four map2s are rotated, cut and spliced, and new fusion parameters need to be created between map2 and B in the overlapping areas. In order to reduce the amount of calculation, the resolution of the ring view can be appropriately reduced, and the 2048x2048 ring view can be downsampled to obtain a 1024x1024 ring view. At this time, one pixel in the ring view represents 2cm, so the original Map can be initialized to 6x1024x1024, where 6 represents the dimension of the array [c,x1,y1,x2,y2,ɑ]. Based on Figure 3 The condition of c is set to calculate the overlapping area, and finally the four map2 and B are merged together to get Map. The calculation formula of α is as follows:

[0135]

[0136] Among them, dist represents the Euclidean distance, dist(px,c1) represents the Euclidean distance of (px,c1), dist(px,c2) represents the Euclidean distance of (px,c2), px is the pixel coordinate in the gray area, c1\c2 represents the geometric center coordinates of the two connected dotted areas, s represents the fusion area of ​​all viewing areas, and s includes (s1,s2,s3,s4).

[0137] This application is based on the above S61-S62 to achieve the fusion from the original image directly to the surround stitching image. In the embodiment of this application, based on the above tire pressure value group TPs, four tire pressure values ​​are set to the above values ​​at the same time, and 10 groups of front, back, left and right fisheye images imgs are recorded. The 10 groups of fisheye images in imgs are obtained by Map, and the mapping relationship between the TP value in TPs and the Map is established. Finally, according to the actual tire pressure of the target vehicle, the average TPm of these four tire pressure values ​​is taken to see which small segment this TPm belongs to in TPr, and then the corresponding TP value in TPs is matched. According to the TP value, which Map is needed for surround stitching in the current vehicle state to complete the surround stitching based on tire pressure monitoring.

[0138] The protection scope of the dynamic surround view stitching method based on tire pressure monitoring described in the embodiment of the present application is not limited to the execution order of the steps listed in the present embodiment. All solutions implemented by adding, reducing or replacing steps in the prior art based on the principles of the present application are included in the protection scope of the present application.

[0139] An embodiment of the present application also provides a dynamic surround view stitching system based on tire pressure monitoring, and the dynamic surround view stitching system based on tire pressure monitoring can implement the dynamic surround view stitching method based on tire pressure monitoring described in the present application. However, the implementation device of the dynamic surround view stitching method based on tire pressure monitoring described in the present application includes but is not limited to the structure of the dynamic surround view stitching system based on tire pressure monitoring listed in the present embodiment. All structural deformations and replacements of the prior art made according to the principles of the present application are included in the protection scope of the present application.

[0140] like Figure 6 As shown, this embodiment provides a dynamic surround view stitching system based on tire pressure monitoring, and the system 3 includes: a tire pressure value quantization processing module 31, a mapping relationship table construction module 32, a target mapping relationship table acquisition module 33 and a surround view stitching module 34.

[0141] The tire pressure value quantization processing module 31 is used to perform tire pressure value quantization processing according to preset vehicle information of the target vehicle to obtain a tire pressure data segment array of the target vehicle; the tire pressure data segment array includes a plurality of tire pressure data segments;

[0142] The mapping relationship table construction module 32 is used to construct a mapping relationship table for each tire pressure data segment according to each tire pressure data segment to obtain a total mapping relationship table;

[0143] The target mapping relationship table acquisition module 33 is used to perform a matching search based on the real-time tire pressure data of the target vehicle and the total mapping relationship table to acquire the target mapping relationship table of the real-time tire pressure data;

[0144] The surround view stitching module 34 is used to perform surround view stitching of the target vehicle according to the target mapping relationship table.

[0145] It should be noted that the functions or operations of the tire pressure value quantization processing module 31, the mapping relationship table construction module 32, the target mapping relationship table acquisition module 33 and the surround view stitching module 34 described in the embodiment of the present disclosure correspond one by one to the steps in the dynamic surround view stitching method based on tire pressure monitoring described above, so they will not be repeated here.

[0146] In the several embodiments provided in the present application, it should be understood that the disclosed system, device or method can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of modules / units is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or units 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 an indirect coupling or communication connection through some interfaces, devices or modules or units, which can be electrical, mechanical or other forms.

[0147] The modules / units described as separate components may or may not be physically separated, and the components displayed as modules / units may or may not be physical modules, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules / units may be selected according to actual needs to achieve the purpose of the embodiments of the present application. For example, the functional modules / units in the various embodiments of the present application may be integrated into one processing module, or each module / unit may exist physically separately, or two or more modules / units may be integrated into one module / unit.

[0148] Those of ordinary skill in the art should further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0149] The embodiment of the present application further provides an electronic device, the electronic device comprising: a memory and a processor; wherein:

[0150] The memory is used to store computer programs;

[0151] The memory includes: ROM, RAM, disk, USB flash drive, memory card or CD and other media that can store program codes.

[0152] The processor is used to execute the computer program stored in the memory, so that the electronic device executes the dynamic surround view stitching method based on tire pressure monitoring as described above.

[0153] Preferably, the processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0154] like Figure 7 As shown, the electronic device 4 of the present application is in the form of a general computing device. The components of the control terminal may include but are not limited to: one or more processors or processing units 41, a memory 42, and a bus 43 connecting different system components (including the memory 42 and the processing unit 41).

[0155] Bus 43 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0156] The control terminal typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the control terminal, including volatile and non-volatile media, removable and non-removable media.

[0157] The memory 42 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 421 and / or cache memory 422. The control terminal may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the memory 42 may be used to read and write non-removable, non-volatile magnetic media ( Figure 7 not shown, usually called a "hard drive"). Although Figure 7Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 43 via one or more data medium interfaces. The memory 42 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present disclosure.

[0158] A program / utility 424 having a set (at least one) of program modules 4241 may be stored, for example, in the memory 42, such program modules 4241 including but not limited to an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 4241 generally perform the functions and / or methods of the embodiments described in the present disclosure.

[0159] The control terminal may also communicate with one or more external devices (e.g., keyboards, pointing devices, displays, etc.), one or more devices that enable a user to interact with the control terminal, and / or any device that enables the control terminal to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed via input / output (I / O) interface 44. Furthermore, the control terminal may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via network adapter 45. Figure 7 As shown, the network adapter 45 communicates with other modules of the control terminal via the bus 43. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the control terminal, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0160] The present application embodiment also provides a computer-readable storage medium. A person of ordinary skill in the art can understand that all or part of the steps in the method for implementing the above embodiment can be completed by a program to instruct the processor, and the program can be stored in a computer-readable storage medium, and the storage medium is a non-transitory medium, such as a random access memory, a read-only memory, a flash memory, a hard disk, a solid-state hard disk, a magnetic tape, a floppy disk, an optical disc, and any combination thereof. The above storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that includes one or more available media integrated. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a digital video disc (DVD)), or a semiconductor medium (e.g., a solid-state hard disk (SSD)), etc.

[0161] The present application embodiment may also provide a computer program product, the computer program product including one or more computer instructions. When the computer instructions are loaded and executed on a computing device, the process or function described in the embodiment of the present application is generated in whole or in part. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from a website site, computer or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer or data center.

[0162] When the computer program product is executed by a computer, the computer executes the method described in the above method embodiment. The computer program product may be a software installation package, and when the above method is required, the computer program product may be downloaded and executed on a computer.

[0163] In summary, the dynamic surround view stitching method and system based on tire pressure monitoring described in this application have the following beneficial effects:

[0164] The present application performs quantification processing of tire pressure values ​​according to preset vehicle information of the target vehicle to obtain a segmented array of tire pressure data of the target vehicle; the segmented array of tire pressure data includes a plurality of tire pressure data segments; a mapping relationship table of each tire pressure data segment is constructed according to each tire pressure data segment to obtain a total mapping relationship table; a matching search is performed according to the real-time tire pressure data of the target vehicle and the total mapping relationship table to obtain a target mapping relationship table of the real-time tire pressure data; and a surround view splicing of the target vehicle is performed according to the target mapping relationship table. The present application reduces the amount of calculation of the Map lookup table caused by frequent changes in tire pressure values ​​by quantifying the tire pressure values ​​in the tire pressure monitoring system, and also reduces the amount of calculation for subsequently establishing a mapping relationship between tire pressure values ​​and Maps.

[0165] The present application obtains a mapping relationship table by performing calculations based on the tire pressure value array, and establishes the entire surround-view stitching process of obtaining the BEV bird's-eye view from distortion correction, perspective transformation, and alpha fusion as a total lookup table Map, and maps the pixels at specified positions in the four original images to the BEV bird's-eye view, thereby reducing the calculations of distortion correction, perspective transformation, and alpha fusion, and does not rely on the high computing power brought by the GPU. The surround-view stitching runs fast and is easy to port to mobile terminals.

[0166] The present application obtains a mapping relationship table by performing calculations based on the tire pressure value array, and establishes the entire surround-view stitching process of the BEV bird's-eye view obtained from distortion correction, perspective transformation, and alpha fusion as a total lookup table Map, directly indexes the pixels in the original image to the BEV bird's-eye view, and then establishes a mapping relationship between the tire pressure values ​​directly from the automobile tire pressure monitoring system and the total lookup table Map, thereby realizing a dynamic surround-view stitching algorithm based on tire pressure monitoring.

[0167] The descriptions of the processes or structures corresponding to the above-mentioned figures have different emphases. For parts that are not described in detail in a certain process or structure, please refer to the relevant descriptions of other processes or structures.

[0168] The above embodiments are merely illustrative of the principles and effects of the present application and are not intended to limit the present application. Anyone familiar with the technology may modify or change the above embodiments without violating the spirit and scope of the present application. Therefore, all equivalent modifications or changes made by a person of ordinary skill in the art without departing from the spirit and technical ideas disclosed in the present application shall still be covered by the claims of the present application.

Claims

1. A dynamic surround view stitching method based on tire pressure monitoring, characterized in that: The method comprises: Performing tire pressure value quantization processing according to preset vehicle information of the target vehicle to obtain a tire pressure data segment array of the target vehicle; the tire pressure data segment array includes a plurality of tire pressure data segments; Constructing mapping relationship tables for each tire pressure data segment according to each tire pressure data segment to obtain a total mapping relationship table; Performing a match search based on the real-time tire pressure data of the target vehicle and the total mapping relationship table to obtain a target mapping relationship table for the real-time tire pressure data; The surround view stitching of the target vehicle is performed according to the target mapping relationship table.

2. The dynamic surround view stitching method based on tire pressure monitoring according to claim 1, characterized in that: The preset vehicle information includes images from various viewing angles and corresponding tire pressure data; The tire pressure value is quantified according to the preset vehicle information of the target vehicle to obtain a segmented array of tire pressure data of the target vehicle, including: Performing pressurization and / or decompression processing according to the images at each viewing angle and corresponding tire pressure data to obtain an image offset relationship; The tire pressure value is quantified according to the image offset relationship to obtain a segmented array of tire pressure data of the target vehicle.

3. The dynamic surround view stitching method based on tire pressure monitoring according to claim 2, characterized in that: Performing pressurization and / or decompression processing according to the images of each viewing angle and the corresponding tire pressure data to obtain the image offset relationship includes: Calibrate the target vehicle through grid calibration according to the images of each viewing angle to obtain first coordinate data of the target vehicle; the first coordinate data includes coordinates of calibration corner points of each viewing angle; Performing pressurization and / or decompression processing at a preset pace according to the tire pressure data to obtain second coordinate data of the target vehicle; the second coordinate data includes the coordinates of the calibrated corner points of each viewing angle after the pressurization and / or decompression processing; Performing Euclidean distance calculation according to the first coordinate data and the second coordinate data to obtain a first Euclidean distance group; the first Euclidean distance group includes the Euclidean distances of the calibrated corner points of each viewing angle before and after the pressurization and / or decompression treatment; Iterate the process in sequence to obtain N groups of Euclidean distance groups; where N>=1 and is an integer; Calculating the average value of the N groups of Euclidean distances to obtain an average value; The image offset relationship is obtained according to the average value.

4. The dynamic surround view stitching method based on tire pressure monitoring according to claim 2, characterized in that: The tire pressure value quantization processing is performed according to the image offset relationship to obtain a segmented array of tire pressure data of the target vehicle, including: Performing pixel conversion according to the image offset relationship to obtain tire pressure error; A segmented array of tire pressure data of the target vehicle is obtained according to the tire pressure error and a preset tire pressure range.

5. The dynamic surround view stitching method based on tire pressure monitoring according to claim 1, characterized in that: According to each of the tire pressure data segments, a mapping relationship table for each of the tire pressure data segments is constructed to obtain a total mapping relationship table including: respectively acquiring target tire pressure data of each tire pressure data segment according to each tire pressure data segment; respectively acquiring images of corresponding viewing angles according to target tire pressure data of each tire pressure data segment; A mapping relationship table of each tire pressure data segment is constructed according to the images of each viewing angle respectively to obtain a total mapping relationship table.

6. The dynamic surround view stitching method based on tire pressure monitoring according to claim 5, characterized in that: The mapping relationship tables of the tire pressure data segments are respectively constructed according to the images of the respective viewing angles to obtain a total mapping relationship table including: Performing distortion correction processing on the images at each viewing angle to obtain correction data at each viewing angle; the correction data includes a correction image and a distortion correction lookup table; Performing perspective transformation processing according to the corrected image of each viewing angle and the corresponding calibrated corner points to obtain perspective transformation data of each viewing angle; the perspective transformation data includes a perspective transformation matrix and a corresponding bird's-eye view image; Performing fusion processing on the bird's-eye view images of each viewing angle to obtain a fusion matrix; Perform fusion processing according to the distortion correction lookup table of each viewing angle, the perspective transformation matrix of each viewing angle and the fusion matrix to obtain a mapping relationship table corresponding to the current tire pressure data segment; The mapping relationship table corresponding to each tire pressure data segment is used as the total mapping relationship table.

7. The dynamic surround view stitching method based on tire pressure monitoring according to claim 6, characterized in that: The distortion correction lookup table of each viewing angle, the perspective transformation matrix of each viewing angle and the fusion matrix are fused to obtain the mapping relationship table corresponding to the current tire pressure data segment, including: Performing fusion processing according to the distortion correction lookup table of each viewing angle and the perspective transformation matrix of each viewing angle to obtain fusion data of each viewing angle; the fusion data includes the fusion lookup table and the viewing angle area; the viewing angle area includes a fusion area and a non-fusion area; A fusion parameter is established according to the fusion lookup table of each viewing angle, the fusion area of ​​each viewing angle and the fusion matrix to obtain the mapping relationship table corresponding to each set of tire pressure data; wherein the fusion parameter is: Among them, dist represents the Euclidean distance, px is the pixel coordinate in the fusion area of ​​each viewing area, c1 and c2 represent the geometric center coordinates of two adjacent viewing areas, and s represents the fusion area of ​​all viewing areas.

8. The dynamic surround view stitching method based on tire pressure monitoring according to claim 1, characterized in that: Performing a match search based on the real-time tire pressure data of the target vehicle and the total mapping relationship table to obtain the target mapping relationship table of the real-time tire pressure data includes: Acquiring real-time tire pressure data of the target vehicle; Acquire the tire pressure data segment to which the real-time tire pressure data belongs according to the real-time tire pressure data and the tire pressure data segment array; A matching search is performed based on the tire pressure data segment to which the real-time tire pressure data belongs and the total mapping relationship table to obtain a mapping relationship table corresponding to the tire pressure data segment to which the real-time tire pressure data belongs, and the mapping relationship table is used as the target mapping relationship table for the real-time tire pressure data.

9. The dynamic surround view stitching method based on tire pressure monitoring according to claim 1, characterized in that: Performing surround stitching of the target vehicle according to the target mapping relationship table includes: Acquire images of corresponding viewing angles according to the real-time tire pressure data; Acquire the viewing area of ​​each viewing angle respectively according to the image of each viewing angle; the viewing area includes a fusion area and a non-fusion area; Performing fusion processing on the fusion areas of each adjacent perspective according to the target mapping relationship table to obtain pixel information of the fusion areas of each adjacent perspective; Calculation is performed according to the target mapping relationship table and the non-fused area of ​​each viewing angle to obtain pixel information of the non-fused area of ​​each viewing angle; Surround view stitching is performed according to the pixel information of the fused area of ​​each adjacent perspective and the non-fused area of ​​each perspective to obtain a target surround view stitching map.

10. A dynamic surround view stitching system based on tire pressure monitoring, characterized in that: The system comprises: A tire pressure value quantification processing module is used to perform tire pressure value quantification processing according to preset vehicle information of a target vehicle to obtain a tire pressure data segment array of the target vehicle; the tire pressure data segment array includes a plurality of tire pressure data segments; A mapping relationship table construction module, used to construct a mapping relationship table for each tire pressure data segment according to each tire pressure data segment, so as to obtain a total mapping relationship table; A target mapping relationship table acquisition module is used to perform a match search based on the real-time tire pressure data of the target vehicle and the total mapping relationship table to acquire a target mapping relationship table for the real-time tire pressure data; A surround view stitching module is used to perform surround view stitching of the target vehicle according to the target mapping relationship table.

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