CN110991232A - Vehicle position correction method and system, storage medium and terminal - Google Patents
Vehicle position correction method and system, storage medium and terminal Download PDFInfo
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- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
- G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
- G06V20/584—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads of vehicle lights or traffic lights
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Abstract
The invention provides a vehicle position correction method and system, a storage medium and a terminal, comprising the following steps: acquiring a two-dimensional image which is acquired by a vehicle-mounted camera device and contains a target vehicle; performing image recognition on the two-dimensional image to acquire the vehicle type and the wheel type of the 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; and correcting the position of the vehicle according to the position information of the vehicle type, the wheel type and the wheel grounding point in a world coordinate system. The vehicle position correction method and system, the storage medium and the terminal realize accurate correction of the vehicle position by restraining the position of the vehicle through the wheel grounding point, thereby improving the detection precision of the vehicle.
Description
Technical Field
The present invention relates to the field of image processing technologies, and in particular, to a method and a system for correcting a vehicle position, 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, position information of surrounding vehicles is 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 vehicle position correction method and system, a storage medium, and a terminal, which achieve accurate correction of a vehicle position by restraining the position of the vehicle by a wheel grounding point, thereby improving detection accuracy of the vehicle.
To achieve the above and other related objects, the present invention provides a vehicle position correction method, including the steps of: acquiring a two-dimensional image which is acquired by a vehicle-mounted camera device and contains a target vehicle; performing image recognition on the two-dimensional image to acquire the vehicle type and the wheel type of the 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; and correcting the position of the vehicle according to the position information of the vehicle type, the wheel type and the wheel grounding point in a world coordinate system.
In an embodiment of the present invention, the vehicle category includes one or more combinations of cars, trucks, buses, and vans; the wheel categories include a front left wheel, a front right wheel, a rear left wheel, and a rear right wheel.
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.
In an embodiment of the present invention, the step of correcting the vehicle position according to the position information of the vehicle type, the wheel type and the wheel grounding point in the world coordinate system includes the steps of:
according to the vehicle type, acquiring a vehicle front overhang length, a vehicle rear overhang length and a wheel track width ratio corresponding to the target vehicle;
calculating the length of the vehicle according to the length of the front overhang of the vehicle, the wheelbase and the rear overhang of the vehicle, wherein the wheelbase is the connecting length of the grounding point of the front wheel and the grounding point of the rear wheel;
and calculating the width of the vehicle according to the width-to-track width ratio, wherein the track is the length of a connecting line between the grounding points of the front wheels or the length of a connecting line between the grounding points of the rear wheels.
In an embodiment of the present invention, the step of correcting the vehicle position according to the position information of the vehicle type, the wheel type and the wheel grounding point in the world coordinate system includes the steps of:
according to the vehicle category, acquiring a vehicle front overhang length, a vehicle rear overhang length, a wheel base and a wheel base width ratio corresponding to the target vehicle; the wheel base is the length of a connecting line between the grounding points of the front wheels and the grounding points of the rear wheels, and the wheel base is the length of a connecting line between the grounding points of the front wheels or the length of a connecting line between the grounding points of the rear wheels;
and constructing the position of the vehicle by taking one or more wheel grounding points as a reference according to the heading angle of the vehicle, wherein the vehicle length is the front suspension length of the vehicle, the wheel base and the rear suspension length of the vehicle, and the vehicle width is the wheel base and the wheel base width ratio.
Correspondingly, the invention provides a vehicle position correction system, which comprises an image acquisition module, an image identification module, a position acquisition module, a conversion module and a correction module, wherein the image acquisition module is used for acquiring images of vehicles;
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 image recognition module is used for carrying out image recognition on the two-dimensional image to acquire the vehicle type and the wheel type of the 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 correction module is used for correcting the position of the vehicle according to the vehicle type, the wheel type and the position information of the wheel grounding point in the world coordinate system.
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 position 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 configured to execute the computer program stored in the memory, so as to cause the terminal device to execute the vehicle position correction method.
Finally, the invention provides a vehicle position 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.
As described above, the vehicle position correction method and system, the storage medium, and the terminal according to the present invention have the following advantageous effects:
(1) the position of the vehicle is restrained through the grounding point of the wheel, so that the detection precision of the position of the vehicle is improved;
(2) support multiple motorcycle type, the practicality is strong.
Drawings
FIG. 1 is a flow chart illustrating a vehicle position correction method according to an embodiment of the present invention;
FIG. 2(a) is a schematic diagram showing the relationship between the length of a car and various parameters;
FIG. 2(b) is a schematic diagram showing the relationship between the length of the minibus and various parameters;
FIG. 2(c) is a schematic diagram showing the relationship between the length of the large truck and various parameters;
FIG. 2(d) is a schematic diagram showing the relationship between the length of the bus and various parameters;
FIG. 3 is a schematic diagram of a vehicle position correcting system according to an embodiment of the invention;
fig. 4 is a schematic structural diagram of a terminal according to an embodiment of the invention;
FIG. 5 is a schematic structural diagram of a vehicle position correction system according to another embodiment of the present invention.
Description of the element reference numerals
31 image acquisition module
32 image recognition module
33 position acquisition module
34 conversion module
35 correction module
41 processor
42 memory
51 terminal
52 vehicle-mounted imaging 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 vehicle position correction method and system, 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 in acquiring 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 one embodiment, the vehicle position correction method 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, performing image recognition on the two-dimensional image to acquire the vehicle type and the wheel type of the target vehicle.
Specifically, for each two-dimensional image, the vehicle and the wheels in the two-dimensional image are detected based on a deep learning algorithm, so that the categories of the vehicle and the wheels are obtained. Preferably, convolutional neural networks such as ResNet or Hourglass are used for image feature extraction, so as to obtain the categories of the vehicle and the wheel. The category of the vehicle may include, among others, cars, lorries, buses, and vans. The categories of wheels may include a front left wheel, a front right wheel, a rear left wheel, and a rear right wheel. Taking ResNet as an example, firstly cutting the two-dimensional image, continuously performing 4 times of downsampling, and then performing 3 times of upsampling to obtain a feature map; and then extracting the vehicle type and the wheel type according to the characteristic diagram.
And step S3, 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:
31) 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 a two-dimensional detection frame of the vehicle and the wheel is obtained.
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.
32) 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 S4, 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 S5, correcting the vehicle position according to the position information of the vehicle type, the wheel type and the wheel grounding point in the world coordinate system.
Specifically, due to angular issues, the number of wheels detected in the two-dimensional image may be one or more. The position of the vehicle can be modified in different ways for different numbers of wheels, different positions.
In an embodiment of the present invention, when four wheels are identified, the step of correcting the vehicle position according to the position information of the vehicle type, the wheel type and the wheel grounding point in the world coordinate system includes the following steps:
a) and acquiring the front overhang length, the rear overhang length and the wheel track width ratio of the target vehicle according to the vehicle category.
b) And calculating the length of the vehicle according to the length of the front suspension of the vehicle, the wheelbase and the rear suspension of the vehicle, wherein the wheelbase is the connecting length of the grounding point of the front wheel and the grounding point of the rear wheel. As shown in fig. 2(a) -2 (d), different types of vehicles correspond to different front overhang lengths and rear overhang lengths.
c) And calculating the width of the vehicle according to the width-to-track width ratio, wherein the track is the length of a connecting line between the grounding points of the front wheels or the length of a connecting line between the grounding points of the rear wheels.
In an embodiment of the present invention, when one or more wheels are identified, the step of correcting the vehicle position according to the position information of the vehicle type, the wheel type and the wheel grounding point in the world coordinate system includes the following steps:
A) according to the vehicle category, acquiring a vehicle front overhang length, a vehicle rear overhang length, a wheel base and a wheel base width ratio corresponding to the target vehicle; the wheel base is the length of a connecting line between the grounding points of the front wheels and the rear wheels, and the wheel base is the length of a connecting line between the grounding points of the front wheels or the length of a connecting line between the grounding points of the rear wheels.
B) And constructing the position of the vehicle by taking one or more wheel grounding points as a reference according to the heading angle of the vehicle, wherein the vehicle length is the front suspension length of the vehicle, the wheel base and the rear suspension length of the vehicle, and the vehicle width is the wheel base and the wheel base width ratio. For a particular type of vehicle, the parameters are fixed, so that the vehicle position can be established by a reference point and direction.
As shown in fig. 3, in one embodiment, the vehicle position correction system of the present invention includes an image acquisition module 31, an image recognition module 32, a position acquisition module 33, a conversion module 34, and a correction module 35.
The image acquisition module 31 is used for 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.
The image recognition module 32 is connected to the image acquisition module 31, and is configured to perform image recognition on the two-dimensional image, and acquire a vehicle type and a wheel type of the target vehicle.
Specifically, for each two-dimensional image, the vehicle and the wheels in the two-dimensional image are detected based on a deep learning algorithm, so that the categories of the vehicle and the wheels are obtained. Preferably, convolutional neural networks such as ResNet or Hourglass are used for image feature extraction, so as to obtain the categories of the vehicle and the wheel. The category of the vehicle may include, among others, cars, lorries, buses, and vans. The categories of wheels may include a front left wheel, a front right wheel, a rear left wheel, and a rear right wheel. Taking ResNet as an example, firstly cutting the two-dimensional image, continuously performing 4 times of downsampling, and then performing 3 times of upsampling to obtain a feature map; and then extracting the vehicle type and the wheel type according to the characteristic diagram.
The position acquiring module 33 is connected to the image recognizing module 32, 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:
31) 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 a two-dimensional detection frame of the vehicle and the wheel is obtained.
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.
32) 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 34 is connected to the position obtaining module 33, and is configured to convert the position information in the camera coordinate system into the 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 correction module 35 is connected to the conversion module 34, and is configured to correct the vehicle position according to the vehicle type, the wheel type, and the position information of the wheel grounding point in the world coordinate system.
Specifically, due to angular issues, the number of wheels detected in the two-dimensional image may be one or more. The position of the vehicle can be modified in different ways for different numbers of wheels, different positions.
In an embodiment of the present invention, when four wheels are identified, the step of correcting the vehicle position according to the position information of the vehicle type, the wheel type and the wheel grounding point in the world coordinate system includes the following steps:
a) and acquiring the front overhang length, the rear overhang length and the wheel track width ratio of the target vehicle according to the vehicle category.
b) And calculating the length of the vehicle according to the length of the front suspension of the vehicle, the wheelbase and the rear suspension of the vehicle, wherein the wheelbase is the connecting length of the grounding point of the front wheel and the grounding point of the rear wheel. As shown in fig. 2(a) -2 (d), different types of vehicles correspond to different front overhang lengths and rear overhang lengths.
c) And calculating the width of the vehicle according to the width-to-track width ratio, wherein the track is the length of a connecting line between the grounding points of the front wheels or the length of a connecting line between the grounding points of the rear wheels.
In an embodiment of the present invention, when one or more wheels are identified, the step of correcting the vehicle position according to the position information of the vehicle type, the wheel type and the wheel grounding point in the world coordinate system includes the following steps:
A) according to the vehicle category, acquiring a vehicle front overhang length, a vehicle rear overhang length, a wheel base and a wheel base width ratio corresponding to the target vehicle; the wheel base is the length of a connecting line between the grounding points of the front wheels and the rear wheels, and the wheel base is the length of a connecting line between the grounding points of the front wheels or the length of a connecting line between the grounding points of the rear wheels.
B) And constructing the position of the vehicle by taking one or more wheel grounding points as a reference according to the heading angle of the vehicle, wherein the vehicle length is the front suspension length of the vehicle, the wheel base and the rear suspension length of the vehicle, and the vehicle width is the wheel base and the wheel base width ratio. For a particular type of vehicle, the parameters are fixed, so that the vehicle position can be established by a reference point and direction.
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 position 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. 4, in an embodiment, the terminal of the present invention includes: a processor 41 and a memory 42.
The memory 42 is used for storing computer programs.
The memory 42 includes: various media that can store program codes, such as ROM, RAM, magnetic disk, U-disk, memory card, or optical disk.
The processor 41 is connected to the memory 42 and is configured to execute the computer program stored in the memory 42, so as to enable the terminal to execute the vehicle position correction method.
Preferably, the Processor 41 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. 5, in an embodiment, the vehicle position correction system of the present invention includes the terminal 51 and the vehicle-mounted camera 52.
The vehicle-mounted camera 52 is connected with the terminal 51, and is configured to collect a two-dimensional image including a target vehicle, and send the two-dimensional image to the terminal 51. And the terminal 51 corrects the position of the vehicle according to the two-dimensional image.
In an embodiment of the present invention, the vehicle-mounted camera 42 employs a fisheye camera.
In summary, the vehicle position correction method and system, the storage medium and the terminal of the present invention restrain the position of the vehicle through the wheel grounding point, thereby improving the detection accuracy of the vehicle position; support multiple motorcycle type, the practicality is strong. 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 vehicle position correction method characterized by: 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;
performing image recognition on the two-dimensional image to acquire the vehicle type and the wheel type of the 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;
and correcting the position of the vehicle according to the position information of the vehicle type, the wheel type and the wheel grounding point in a world coordinate system.
2. The vehicle position correction method according to claim 1, characterized in that: the vehicle category comprises one or more combinations of cars, trucks, buses and bread cars; the wheel categories include a front left wheel, a front right wheel, a rear left wheel, and a rear right wheel.
3. The vehicle position correction method according to claim 1, characterized in that: 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.
4. The vehicle position correction method according to claim 3, characterized in that when a plurality of vehicles are included in the two-dimensional image, it is determined whether a current wheel belongs to the target vehicle based on 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 larger than a preset threshold, it is determined that the current wheel belongs to the target vehicle.
5. The vehicle position correction method according to claim 1, characterized in that: the step of correcting the position of the vehicle according to the position information of the vehicle type, the wheel type and the wheel grounding point in the world coordinate system comprises the following steps:
according to the vehicle type, acquiring a vehicle front overhang length, a vehicle rear overhang length and a wheel track width ratio corresponding to the target vehicle;
calculating the length of the vehicle according to the length of the front overhang of the vehicle, the wheelbase and the rear overhang of the vehicle, wherein the wheelbase is the connecting length of the grounding point of the front wheel and the grounding point of the rear wheel;
and calculating the width of the vehicle according to the width-to-track width ratio, wherein the track is the length of a connecting line between the grounding points of the front wheels or the length of a connecting line between the grounding points of the rear wheels.
6. The vehicle position correction method according to claim 1, characterized in that: the step of correcting the position of the vehicle according to the position information of the vehicle type, the wheel type and the wheel grounding point in the world coordinate system comprises the following steps:
according to the vehicle category, acquiring a vehicle front overhang length, a vehicle rear overhang length, a wheel base and a wheel base width ratio corresponding to the target vehicle; the wheel base is the length of a connecting line between the grounding points of the front wheels and the grounding points of the rear wheels, and the wheel base is the length of a connecting line between the grounding points of the front wheels or the length of a connecting line between the grounding points of the rear wheels;
and constructing the position of the vehicle by taking one or more wheel grounding points as a reference according to the heading angle of the vehicle, wherein the vehicle length is the front suspension length of the vehicle, the wheel base and the rear suspension length of the vehicle, and the vehicle width is the wheel base and the wheel base width ratio.
7. A vehicle position correction system characterized in that: the device comprises an image acquisition module, an image identification module, a position acquisition module, a conversion 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 image recognition module is used for carrying out image recognition on the two-dimensional image to acquire the vehicle type and the wheel type of the 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 correction module is used for correcting the position of the vehicle according to the vehicle type, the wheel type and the position information of the wheel grounding point in the world coordinate system.
8. A computer-readable storage medium characterized by: on which a computer program is stored which, when executed by a processor, implements the vehicle position correction method according to any one of claims 1 to 6.
9. A terminal, characterized by: comprises a processor and a memory;
the memory is used for storing a computer program;
the processor is configured to execute the computer program stored in the memory to cause the terminal device to execute the vehicle position correction method according to any one of claims 1 to 6.
10. A vehicle position correction system characterized in that: comprising the terminal of claim 9 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.
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