CN110962844A - Vehicle course angle correction method and system, storage medium and terminal - Google Patents
Vehicle course angle correction method and system, storage medium and terminal Download PDFInfo
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- CN110962844A CN110962844A CN201911032056.4A CN201911032056A CN110962844A CN 110962844 A CN110962844 A CN 110962844A CN 201911032056 A CN201911032056 A CN 201911032056A CN 110962844 A CN110962844 A CN 110962844A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
- B60W30/06—Automatic manoeuvring for parking
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
Abstract
The invention provides a method and a system for correcting a vehicle course angle, a storage medium and a terminal, which comprise the following steps: acquiring a two-dimensional image which is acquired by a vehicle-mounted camera device and contains a target vehicle; acquiring position information of a wheel grounding point of the target vehicle in the two-dimensional image under a camera coordinate system; converting the position information under the camera coordinate system into position information under a world coordinate system; acquiring course angle information of the target vehicle according to a connecting line of two wheel grounding points positioned on the same side under a world coordinate system; and correcting the course angle of the target vehicle acquired in the three-dimensional target detection process based on the course angle information. The method and the system for correcting the vehicle course angle, the storage medium and the terminal realize accurate correction of the vehicle course angle by restraining the vehicle course angle through the wheel grounding point, thereby improving the detection precision of the vehicle.
Description
Technical Field
The invention relates to the technical field of image processing, in particular to a method and a system for correcting a vehicle course angle, a storage medium and a terminal.
Background
An Advanced Driver Assistance System (ADAS) is an active safety technology that collects environmental data inside and outside a vehicle at a first time by using various sensors mounted on the vehicle, and performs technical processes such as identification, detection, tracking, and the like of static and dynamic objects, so that a Driver can perceive a possible danger at the fastest time, thereby attracting attention and improving safety.
In recent years, ADAS has become accepted by more and more users. Generally, the ADAS collects images around a vehicle body through a wide-angle camera mounted on the vehicle, and provides various advanced driving assistance functions including panoramic parking assistance, lane departure warning, blind area vehicle detection, collision prediction and the like for a driver through algorithm analysis and processing, so that the ADAS has important significance in improving the active safety of the vehicle. Specifically, during the parking process of the vehicle, information such as the distance and the direction of the surrounding vehicle contributes to safe operation of the current vehicle. In the prior art, distance information and direction information of surrounding vehicles are acquired by a three-dimensional vehicle detection method. However, the method has low detection precision, the regression of the target depth and the course angle has certain difficulty, and the problem of inaccurate regression exists, so that the overall detection precision of the three-dimensional vehicle is influenced.
Disclosure of Invention
In view of the above-mentioned drawbacks of the prior art, an object of the present invention is to provide a method and a system for correcting a vehicle heading angle, a storage medium, and a terminal, which can accurately correct the vehicle heading angle by constraining the vehicle heading angle through a wheel grounding point, thereby improving the detection accuracy of the vehicle.
In order to achieve the above objects and other related objects, the present invention provides a method for correcting a vehicle heading angle, comprising the steps of: acquiring a two-dimensional image which is acquired by a vehicle-mounted camera device and contains a target vehicle; acquiring position information of a wheel grounding point of the target vehicle in the two-dimensional image under a camera coordinate system; converting the position information under the camera coordinate system into position information under a world coordinate system; acquiring course angle information of the target vehicle according to a connecting line of two wheel grounding points positioned on the same side under a world coordinate system; and correcting the course angle of the target vehicle acquired in the three-dimensional target detection process based on the course angle information.
In an embodiment of the present invention, the obtaining of the position information of the wheel grounding point of the target vehicle in the two-dimensional image under the camera coordinate system includes the following steps:
obtaining a wheel detection frame of the target vehicle in the two-dimensional image based on a deep learning algorithm;
and acquiring the position information of the wheel grounding point under a camera coordinate system based on the wheel detection frame.
In an embodiment of the present invention, when the two-dimensional image includes a plurality of vehicles, whether the current wheel belongs to the target vehicle is determined according to a ratio of (a ∩ B)/B, where a represents an area of the target vehicle detection frame and B represents an area of the current wheel detection frame, and when the ratio is greater than a preset threshold, it is determined that the current wheel belongs to the target vehicle.
Correspondingly, the invention provides a vehicle course angle correction system, which comprises an image acquisition module, a position acquisition module, a conversion module, a course angle acquisition module and a correction module, wherein the image acquisition module is used for acquiring a position of a vehicle;
the image acquisition module is used for acquiring a two-dimensional image which is acquired by the vehicle-mounted camera device and contains a target vehicle;
the position acquisition module is used for acquiring position information of a wheel grounding point of the target vehicle in the two-dimensional image under a camera coordinate system;
the conversion module is used for converting the position information under the camera coordinate system into position information under a world coordinate system;
the course angle acquisition module is used for acquiring course angle information of the target vehicle according to a connection line of two wheel grounding points positioned on the same side under a world coordinate system;
the correction module is used for correcting the course angle of the target vehicle acquired in the three-dimensional target detection process based on the course angle information.
In an embodiment of the present invention, the step of acquiring the position information of the wheel grounding point of the target vehicle in the two-dimensional image under the camera coordinate system by the position acquisition module includes the following steps:
obtaining a wheel detection frame of the target vehicle in the two-dimensional image based on a deep learning algorithm;
and acquiring the position information of the wheel grounding point under a camera coordinate system based on the wheel detection frame.
In an embodiment of the present invention, when the two-dimensional image includes a plurality of vehicles, whether a wheel belongs to the target vehicle is determined according to a ratio of (a ∩ B)/B, where a represents an area of a vehicle detection frame and B represents an area of a wheel detection frame, and when the ratio is greater than a preset threshold, it is determined that the current wheel belongs to the target vehicle.
The present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the above-described vehicle heading angle correction method.
The invention provides a terminal, which comprises a processor and a memory;
the memory is used for storing a computer program;
the processor is used for executing the computer program stored in the memory so as to enable the terminal equipment to execute the vehicle course angle correction method.
Finally, the invention provides a vehicle course angle correction system, which comprises the terminal and a vehicle-mounted camera device;
the vehicle-mounted camera device is used for collecting two-dimensional images containing the target vehicle and sending the two-dimensional images to the terminal.
In an embodiment of the present invention, the vehicle-mounted camera device employs a fisheye camera.
As described above, the method and system for correcting the vehicle heading angle, the storage medium, and the terminal of the present invention have the following advantageous effects:
(1) the heading angle of the vehicle is restrained through the grounding point of the wheel, so that the further correction of the heading angle of the vehicle obtained by the three-dimensional target detection is realized;
(2) the detection precision of the vehicle is greatly improved.
Drawings
FIG. 1 is a flowchart illustrating a method for correcting a vehicle heading angle according to an embodiment of the invention;
FIG. 2 is a schematic structural diagram of a vehicle course angle corrector system according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a terminal according to an embodiment of the invention;
FIG. 4 is a schematic structural diagram of a vehicle heading angle correction system according to another embodiment of the invention.
Description of the element reference numerals
21 image acquisition module
22 position acquisition module
23 conversion module
24 course angle acquisition module
25 correction module
31 processor
32 memory
41 terminal
42 vehicle-mounted image pickup device
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present invention, and the components related to the present invention are only shown in the drawings rather than drawn according to the number, shape and size of the components in actual implementation, and the type, quantity and proportion of the components in actual implementation may be changed freely, and the layout of the components may be more complicated.
The method and the system for correcting the vehicle course angle, the storage medium and the terminal realize accurate correction of the vehicle course angle by restraining the vehicle course angle through the wheel grounding point, effectively overcome the defect of low accuracy of the existing three-dimensional vehicle detection method for collecting the vehicle course angle, greatly improve the detection accuracy of the vehicle and provide information support for intelligent auxiliary driving functions such as automatic parking, collision prediction and the like.
As shown in fig. 1, in an embodiment, the method for correcting the vehicle heading angle of the present invention includes the following steps:
and step S1, acquiring a two-dimensional image which is acquired by the vehicle-mounted camera device and contains the target vehicle.
Specifically, a vehicle-mounted camera device is arranged on the vehicle, and two-dimensional images around the vehicle can be collected in real time. Preferably, the vehicle-mounted camera device adopts a fisheye camera. The fisheye camera can independently realize monitoring without dead angles in a large range and is also called as a panoramic camera.
In the invention, the vehicle-mounted camera device collects a two-dimensional image containing a target vehicle and sends the two-dimensional image to the terminal in a wired or wireless mode. It should be noted that the two-dimensional image may include one or more vehicles, or one or more vehicles may be selected from the two-dimensional image as the target vehicle.
And step S2, acquiring the position information of the wheel grounding point of the target vehicle in the two-dimensional image under a camera coordinate system.
Specifically, for the two-dimensional image, firstly, target identification is required, that is, the wheels in the two-dimensional image are identified; then, acquiring a wheel detection frame of the wheel to indicate the overall position of the wheel; then determining a wheel grounding point in the wheel detection frame; finally, the wheel grounding point is projected on a top view, so that the position information of the wheel grounding point under a camera coordinate system is obtained. The wheel grounding point refers to the middle point of the lower bottom edge of the wheel frame. The camera coordinate system is a three-dimensional rectangular coordinate system established by taking the focusing center of the camera as an origin and taking the optical axis as the Z axis. Specifically, the origin of the camera coordinate system is the optical center of the camera, the X-axis and the Y-axis are parallel to the X-axis and the Y-axis of the image, and the z-axis is the optical axis of the camera and is perpendicular to the graphic plane.
In an embodiment of the present invention, the obtaining of the position information of the wheel grounding point of the target vehicle in the two-dimensional image under the camera coordinate system includes the following steps:
21) and acquiring a wheel detection frame of the target vehicle in the two-dimensional image based on a deep learning algorithm.
And for each two-dimensional image, detecting the vehicle and the wheels based on a deep learning algorithm, so as to obtain the category of the vehicle and the wheels and a two-dimensional detection frame. Preferably, convolutional neural networks such as ResNet or Hourglass are used for image feature extraction, so that the categories and two-dimensional detection frames of the vehicle and the wheel are obtained. The category of the vehicle may include, among others, cars, lorries, buses, and vans. The category of wheels may include front wheels and rear wheels.
When only one vehicle is included in the two-dimensional image, all the detected wheels belong to the vehicle. When the two-dimensional image includes two or more vehicles, the dependency relationship between the vehicles and the wheels needs to be obtained.
In an embodiment of the present invention, when the two-dimensional image includes a plurality of vehicles, it is determined whether the current wheel belongs to the target vehicle according to a ratio of (a ∩ B)/B, where a represents an area of the target vehicle detection frame, and B represents an area of the current wheel detection frame, and the specific address is determined that the current wheel belongs to the target vehicle when the ratio is greater than a preset threshold, and that the current wheel does not belong to the target vehicle when the ratio is not greater than the preset threshold.
22) And acquiring the position information of the wheel grounding point under a camera coordinate system based on the wheel detection frame.
Specifically, the wheel grounding point is determined according to the wheel detection frame, and the wheel grounding point is projected on a top view, so that the position information of the wheel grounding point in the camera coordinate system can be acquired.
And step S3, converting the position information in the camera coordinate system into position information in a world coordinate system.
Specifically, the world coordinate system is the absolute coordinate system of the system, and the coordinates of all points on the screen before the user coordinate system is established are the origin of the coordinate system to determine the respective positions. The transformation from the camera coordinate system to the world coordinate system can be realized by rotating the matrix R and translating the matrix T, which is not described herein again.
And step S4, acquiring the course angle information of the target vehicle according to the connecting line of the grounding points of the two wheels positioned on the same side under the world coordinate system.
Specifically, for the target vehicle, two wheel grounding points located on the same side need to be selected from the detected wheels. And connecting the two vehicle grounding points on the same side, and obtaining the course angle information of the target vehicle according to the vehicle running direction and the connecting line. When the target vehicle is detected to have two or more wheel grounding points, whether the two wheel grounding points are positioned on the same side of the vehicle is judged through course angle information obtained in a deep learning algorithm.
And step S5, correcting the course angle of the target vehicle obtained in the three-dimensional target detection process based on the course angle information.
Specifically, for the target vehicle, a course angle which may have a deviation can be obtained through a three-dimensional target detection algorithm, and the obtained course angle information is used for correcting the course angle, so that the detection precision of the course angle obtained through the three-dimensional target detection algorithm is improved.
As shown in FIG. 2, in one embodiment, the system for correcting the vehicle heading angle of the present invention includes an image obtaining module 21, a position obtaining module 22, a converting module 23, a heading angle obtaining module 24, and a correcting module 25.
The image obtaining module 22 is configured to obtain a two-dimensional image including a target vehicle, which is collected by the vehicle-mounted camera device.
Specifically, a vehicle-mounted camera device is arranged on the vehicle, and two-dimensional images around the vehicle can be collected in real time. Preferably, the vehicle-mounted camera device adopts a fisheye camera. The fisheye camera can independently realize monitoring without dead angles in a large range and is also called as a panoramic camera.
In the invention, the vehicle-mounted camera device collects a two-dimensional image containing a target vehicle and sends the two-dimensional image to the terminal in a wired or wireless mode. It should be noted that the two-dimensional image may include one or more vehicles, or one or more vehicles may be selected from the two-dimensional image as the target vehicle.
The position acquisition module 22 is connected to the image acquisition module 21, and is configured to acquire position information of a wheel grounding point of the target vehicle in the two-dimensional image in a camera coordinate system.
Specifically, for the two-dimensional image, firstly, target identification is required, that is, the wheels in the two-dimensional image are identified; then, acquiring a wheel detection frame of the wheel to indicate the overall position of the wheel; then determining a wheel grounding point in the wheel detection frame; finally, the wheel grounding point is projected on a top view, so that the position information of the wheel grounding point under a camera coordinate system is obtained. The wheel grounding point refers to the middle point of the lower bottom edge of the wheel frame. The camera coordinate system is a three-dimensional rectangular coordinate system established by taking the focusing center of the camera as an origin and taking the optical axis as the Z axis. Specifically, the origin of the camera coordinate system is the optical center of the camera, the X-axis and the Y-axis are parallel to the X-axis and the Y-axis of the image, and the z-axis is the optical axis of the camera and is perpendicular to the graphic plane.
In an embodiment of the present invention, the obtaining of the position information of the wheel grounding point of the target vehicle in the two-dimensional image under the camera coordinate system includes the following steps:
21) and acquiring a wheel detection frame of the target vehicle in the two-dimensional image based on a deep learning algorithm.
And for each two-dimensional image, detecting the vehicle and the wheels based on a deep learning algorithm, so as to obtain the category of the vehicle and the wheels and a two-dimensional detection frame. Preferably, convolutional neural networks such as ResNet or Hourglass are used for image feature extraction, so that the categories and two-dimensional detection frames of the vehicle and the wheel are obtained. The category of the vehicle may include, among others, cars, lorries, buses, and vans. The category of wheels may include front wheels and rear wheels.
When only one vehicle is included in the two-dimensional image, all the detected wheels belong to the vehicle. When the two-dimensional image includes two or more vehicles, the dependency relationship between the vehicles and the wheels needs to be obtained.
In an embodiment of the present invention, when the two-dimensional image includes a plurality of vehicles, it is determined whether the current wheel belongs to the target vehicle according to a ratio of (a ∩ B)/B, where a represents an area of the target vehicle detection frame, and B represents an area of the current wheel detection frame, and the specific address is determined that the current wheel belongs to the target vehicle when the ratio is greater than a preset threshold, and that the current wheel does not belong to the target vehicle when the ratio is not greater than the preset threshold.
22) And acquiring the position information of the wheel grounding point under a camera coordinate system based on the wheel detection frame.
Specifically, the wheel grounding point is determined according to the wheel detection frame, and the wheel grounding point is projected on a top view, so that the position information of the wheel grounding point in the camera coordinate system can be acquired.
The conversion module 23 is connected to the image acquisition module 22, and is configured to convert the position information in the camera coordinate system into position information in the world coordinate system.
Specifically, the world coordinate system is the absolute coordinate system of the system, and the coordinates of all points on the screen before the user coordinate system is established are the origin of the coordinate system to determine the respective positions. The transformation from the camera coordinate system to the world coordinate system can be realized by rotating the matrix R and translating the matrix T, which is not described herein again.
The course angle obtaining module 24 is connected to the converting module 23, and is configured to obtain course angle information of the target vehicle according to a connection line of two wheel grounding points located on the same side in the world coordinate system.
Specifically, for the target vehicle, two wheel grounding points located on the same side need to be selected from the detected wheels. And connecting the two vehicle grounding points on the same side, and obtaining the course angle information of the target vehicle according to the vehicle running direction and the connecting line. When the target vehicle is detected to have two or more wheel grounding points, whether the two wheel grounding points are positioned on the same side of the vehicle is judged through course angle information obtained in a deep learning algorithm.
The correcting module 25 is connected to the course angle obtaining module 24, and is configured to correct the course angle of the target vehicle obtained in the three-dimensional target detection process based on the course angle information.
Specifically, for the target vehicle, a course angle which may have a deviation can be obtained through a three-dimensional target detection algorithm, and the obtained course angle information is used for correcting the course angle, so that the detection precision of the course angle obtained through the three-dimensional target detection algorithm is improved.
It should be noted that the division of the modules of the above apparatus is only a logical division, and the actual implementation may be wholly or partially integrated into one physical entity, or may be physically separated. And the modules can be realized in a form that all software is called by the processing element, or in a form that all the modules are realized in a form that all the modules are called by the processing element, or in a form that part of the modules are called by the hardware. For example: the x module can be a separately established processing element, and can also be integrated in a certain chip of the device. In addition, the x-module may be stored in the memory of the apparatus in the form of program codes, and may be called by a certain processing element of the apparatus to execute the functions of the x-module. Other modules are implemented similarly. All or part of the modules can be integrated together or can be independently realized. The processing element described herein may be an integrated circuit having signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in the form of software. These above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), one or more microprocessors (DSPs), one or more Field Programmable Gate Arrays (FPGAs), and the like. When a module is implemented in the form of a processing element scheduler code, the processing element may be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor capable of calling program code. These modules may be integrated together and implemented in the form of a System-on-a-chip (SOC).
The storage medium of the present invention stores thereon a computer program that realizes the above-described vehicle heading angle correction method when executed by a processor. The storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic disk, U-disk, memory card, or optical disk.
As shown in fig. 3, in an embodiment, the terminal of the present invention includes: a processor 31 and a memory 32.
The memory 32 is used for storing computer programs.
The memory 32 includes: various media that can store program codes, such as ROM, RAM, magnetic disk, U-disk, memory card, or optical disk.
The processor 31 is connected to the memory 32 and is configured to execute the computer program stored in the memory 32, so that the terminal executes the above-mentioned vehicle heading angle correction method.
Preferably, the Processor 31 may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; the integrated Circuit may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, or discrete hardware components.
As shown in fig. 4, in an embodiment, the system for correcting the vehicle heading angle of the present invention includes the terminal 41 and the vehicle-mounted camera 42.
The vehicle-mounted camera 42 is connected to the terminal 41, and is configured to collect a two-dimensional image including a target vehicle, and send the two-dimensional image to the terminal 41. And the terminal 41 corrects the vehicle course angle according to the two-dimensional image.
In an embodiment of the present invention, the vehicle-mounted camera 42 employs a fisheye camera.
In conclusion, the vehicle course angle correction method and system, the storage medium and the terminal restrain the course angle of the vehicle through the wheel grounding point, and further correction of the vehicle course angle obtained by three-dimensional target detection is realized; the detection precision of the vehicle is greatly improved. Therefore, the invention effectively overcomes various defects in the prior art and has high industrial utilization value.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.
Claims (10)
1. A method for correcting a vehicle course angle is characterized by comprising the following steps: the method comprises the following steps:
acquiring a two-dimensional image which is acquired by a vehicle-mounted camera device and contains a target vehicle;
acquiring position information of a wheel grounding point of the target vehicle in the two-dimensional image under a camera coordinate system;
converting the position information under the camera coordinate system into position information under a world coordinate system;
acquiring course angle information of the target vehicle according to a connecting line of two wheel grounding points positioned on the same side under a world coordinate system;
and correcting the course angle of the target vehicle acquired in the three-dimensional target detection process based on the course angle information.
2. The vehicle heading angle correction method according to claim 1, wherein: acquiring position information of a wheel grounding point of the target vehicle in the two-dimensional image under a camera coordinate system comprises the following steps:
obtaining a wheel detection frame of the target vehicle in the two-dimensional image based on a deep learning algorithm;
and acquiring the position information of the wheel grounding point under a camera coordinate system based on the wheel detection frame.
3. The method for correcting the vehicle heading angle according to claim 2, wherein when the two-dimensional image includes a plurality of vehicles, it is determined whether a current wheel belongs to the target vehicle according to a ratio of (A ∩ B)/B, wherein A represents an area of the target vehicle detection frame and B represents an area of the current wheel detection frame, and when the ratio is greater than a preset threshold value, it is determined that the current wheel belongs to the target vehicle.
4. A vehicle course angle correction system, characterized by: the device comprises an image acquisition module, a position acquisition module, a conversion module, a course angle acquisition module and a correction module;
the image acquisition module is used for acquiring a two-dimensional image which is acquired by the vehicle-mounted camera device and contains a target vehicle;
the position acquisition module is used for acquiring position information of a wheel grounding point of the target vehicle in the two-dimensional image under a camera coordinate system;
the conversion module is used for converting the position information under the camera coordinate system into position information under a world coordinate system;
the course angle acquisition module is used for acquiring course angle information of the target vehicle according to a connection line of two wheel grounding points positioned on the same side under a world coordinate system;
the correction module is used for correcting the course angle of the target vehicle acquired in the three-dimensional target detection process based on the course angle information.
5. The vehicle heading angle correction system of claim 4, wherein: the position acquisition module acquiring position information of a wheel grounding point of the target vehicle in the two-dimensional image under a camera coordinate system comprises the following steps:
obtaining a wheel detection frame of the target vehicle in the two-dimensional image based on a deep learning algorithm;
and acquiring the position information of the wheel grounding point under a camera coordinate system based on the wheel detection frame.
6. The vehicle heading angle correcting system according to claim 5, wherein when the two-dimensional image includes a plurality of vehicles, it is determined whether a wheel belongs to the target vehicle based on a ratio (A ∩ B)/B, wherein A represents an area of a vehicle detection frame and B represents an area of a wheel detection frame, and when the ratio is greater than a preset threshold, it is determined that the current wheel belongs to the target vehicle.
7. A computer-readable storage medium characterized by: a computer program stored thereon, which when executed by a processor implements the vehicle heading angle correction method of any one of claims 1 to 3.
8. A terminal, characterized by: comprises a processor and a memory;
the memory is used for storing a computer program;
the processor is used for executing the computer program stored by the memory to enable the terminal device to execute the vehicle heading angle correction method in any one of claims 1 to 3.
9. A vehicle course angle correction system, characterized by: comprising the terminal of claim 8 and an onboard camera; the vehicle-mounted camera device is used for collecting two-dimensional images containing the target vehicle and sending the two-dimensional images to the terminal.
10. The vehicle heading angle correction system of claim 9, wherein: the vehicle-mounted camera device adopts a fisheye camera.
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| CN111950504A (en) * | 2020-08-21 | 2020-11-17 | 东软睿驰汽车技术（沈阳）有限公司 | Vehicle detection method and device and electronic equipment |
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