CN116386000A - Method and system for measuring obstacle distance based on high-precision map and monocular camera - Google Patents
Method and system for measuring obstacle distance based on high-precision map and monocular camera Download PDFInfo
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- 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
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Abstract
The invention provides a method and a system for measuring obstacle distance based on a high-precision map and a monocular camera, wherein the method comprises the following steps: identifying elements on the high-precision map; acquiring an image shot by a monocular camera on a vehicle, and carrying out matching analysis on an obstacle in the image shot by the monocular camera and the identified element on the high-precision map; judging whether the height information of the obstacle is known; if the height information of the obstacle is known, the distance between the obstacle and the vehicle is acquired based on the monocular ranging principle and the height information of the obstacle. The invention can solve the technical problems that the prior art can not independently obtain the distance of the obstacle through the monocular camera, and the size and the direction of the obstacle are required to be known, or the distance of the obstacle can be obtained through the binocular camera.
Description
Technical Field
The invention relates to the technical field of intelligent driving, in particular to a method and a system for measuring obstacle distance based on a high-precision map and a monocular camera.
Background
The automatic driving technology is a product of the integration of technical development of automobile electronics, intelligent control, the Internet and the like, and the principle is that an automatic driving system obtains vehicle information and surrounding environment information through a sensing system and analyzes, calculates and processes the collected data information through a processor, so that a decision control execution system is made to realize actions such as acceleration, deceleration, steering and the like of the vehicle.
The perception system is the eyes of the unmanned vehicle, and the unsafe automatic driving is greatly dependent on the fact that the perception systems do not work well. Monocular cameras are common, cost-effective sensing elements in vehicles. However, due to the limitation of the monocular imaging principle, the prior art cannot obtain the distance of the obstacle through the monocular camera alone, and the size and the direction of the obstacle must be known, or the distance of the obstacle can be obtained through the binocular camera.
Disclosure of Invention
Therefore, an embodiment of the invention provides a method for measuring the distance of an obstacle based on a high-precision map and a monocular camera, so as to solve the technical problems that the distance of the obstacle cannot be obtained by the monocular camera alone in the prior art, the size and the direction of the obstacle are required to be known, or the distance of the obstacle can be obtained by the binocular camera.
According to one embodiment of the invention, the method for measuring the obstacle distance based on the high-precision map and the monocular camera comprises the following steps:
identifying elements on the high-precision map;
acquiring an image shot by a monocular camera on a vehicle, and carrying out matching analysis on an obstacle in the image shot by the monocular camera and the identified element on the high-precision map;
judging whether the height information of the obstacle is known;
if the height information of the obstacle is known, the distance between the obstacle and the vehicle is acquired based on the monocular ranging principle and the height information of the obstacle.
According to the method for measuring the distance between the obstacle based on the high-precision map and the monocular camera, disclosed by the embodiment of the invention, the elements on the high-precision map are firstly identified, then the image shot by the monocular camera on the vehicle is acquired, the obstacle in the image shot by the monocular camera and the identified elements on the high-precision map are subjected to matching analysis, if the height information of the obstacle is known, the distance between the obstacle and the vehicle can be directly acquired based on the monocular distance measurement principle and the height information of the obstacle.
In addition, the method for measuring the obstacle distance based on the high-precision map and the monocular camera according to the embodiment of the invention can also have the following additional technical features:
further, after the step of confirming whether the height information of the obstacle is known, the method further includes:
if the height information of the obstacle is unknown, judging whether the obstacle in the image shot by the monocular camera is matched with the identified element on the high-precision map;
if an obstacle in an image shot by the monocular camera is matched with an element on the identified high-precision map, acquiring the distance between the obstacle and the vehicle based on the monocular distance measurement principle and the information of the high-precision map.
Further, after the step of determining whether the obstacle in the image captured by the monocular camera matches the element on the identified high-precision map, the method further includes:
if the obstacle in the image shot by the monocular camera is not matched with all the elements on the identified high-precision map, further judging whether a lane line exists or not;
if a lane line exists, calculating the distance between the obstacle and the vehicle through the lane line.
Further, the step of calculating the distance between the obstacle and the vehicle through the lane line specifically includes:
the width of the lane is obtained from the high-precision map, and then the distance of the obstacle and the distance between the obstacle and the vehicle are calculated through the pixel points of the lane in the image, the width of the lane, the camera parameters of the monocular camera and the height pixels of the obstacle in the image.
Further, after the step of determining whether a lane line exists, the method further includes:
if the lane line does not exist, judging whether a preset road element exists, wherein the preset road element is any one of a road marking, a crosswalk and a road rod;
if the preset road elements exist, converting the perspective view into a top view through reverse perspective transformation, and then carrying out interpolation change to determine the distance between the lane line calculation obstacle and the vehicle.
Another embodiment of the invention provides a system for measuring the distance of an obstacle based on a high-precision map and a monocular camera, which aims to solve the technical problem that the distance of the obstacle cannot be obtained by the monocular camera alone in the prior art, the size and the direction of the obstacle are required to be known, or the distance of the obstacle can be obtained by the binocular camera.
A system for measuring obstacle distance based on a high-precision map and a monocular camera according to an embodiment of the present invention, the system comprising:
the identification module is used for identifying the elements on the high-precision map;
the acquisition module is used for acquiring an image shot by the monocular camera on the vehicle and carrying out matching analysis on the obstacle in the image shot by the monocular camera and the identified element on the high-precision map;
a first judging module for judging whether the height information of the obstacle is known;
the first calculation module is used for acquiring the distance between the obstacle and the vehicle based on the monocular ranging principle and the height information of the obstacle if the height information of the obstacle is known.
According to the system for measuring the distance between the obstacle based on the high-precision map and the monocular camera, disclosed by the embodiment of the invention, the elements on the high-precision map are firstly identified, then the image shot by the monocular camera on the vehicle is acquired, the obstacle in the image shot by the monocular camera and the identified elements on the high-precision map are subjected to matching analysis, if the height information of the obstacle is known, the distance between the obstacle and the vehicle can be directly acquired based on the monocular distance measurement principle and the height information of the obstacle.
In addition, the system for measuring the obstacle distance based on the high-precision map and the monocular camera according to the embodiment of the invention can also have the following additional technical features:
further, the system further comprises:
the second judging module is used for judging whether the obstacle in the image shot by the monocular camera is matched with the elements on the identified high-precision map or not if the height information of the obstacle is unknown;
and the second calculation module is used for acquiring the distance between the obstacle and the vehicle based on the monocular distance measurement principle and the information of the high-precision map if the obstacle in the image shot by the monocular camera is matched with the identified element on the high-precision map.
Further, the system further comprises:
the third judging module is used for further judging whether a lane line exists or not if the obstacle in the image shot by the monocular camera is not matched with all the elements on the identified high-precision map;
and the third calculation module is used for calculating the distance between the obstacle and the vehicle through the lane line if the lane line exists.
Further, the third computing module is specifically configured to:
the width of the lane is obtained from the high-precision map, and then the distance of the obstacle and the distance between the obstacle and the vehicle are calculated through the pixel points of the lane in the image, the width of the lane, the camera parameters of the monocular camera and the height pixels of the obstacle in the image.
Further, the system further comprises:
a fourth judging module, configured to judge whether a preset road element exists if no lane line exists, where the preset road element is any one of a road marking, a crosswalk, and a road rod;
and the fourth calculation module is used for converting the perspective view into a top view through reverse perspective transformation if the preset road element exists, and then determining the distance between the lane line calculation obstacle and the vehicle through interpolation change.
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The foregoing and/or additional aspects and advantages of embodiments of the invention will be apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:
FIG. 1 is a flow chart of a method of measuring obstacle distance based on a high-precision map and a monocular camera according to an embodiment of the present invention;
FIG. 2 is a schematic view of an obstacle on a roadway;
FIG. 3 is a schematic diagram of the principle of calculating the height of an obstacle and the distance of the obstacle from the camera by similar triangles;
fig. 4 is a schematic structural view of a system for measuring an obstacle distance based on a high-precision map and a monocular camera according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a method for measuring an obstacle distance based on a high-precision map and a monocular camera according to an embodiment of the present invention includes the following steps S1 to S10:
s1, identifying elements on the high-precision map.
S2, acquiring an image shot by a monocular camera on the vehicle, and carrying out matching analysis on an obstacle in the image shot by the monocular camera and the identified element on the high-precision map.
S3, judging whether the height information of the obstacle is known.
And S4, if the height information of the obstacle is known, acquiring the distance between the obstacle and the vehicle based on the monocular distance measurement principle and the height information of the obstacle.
The height of the obstacle can assist in ranging, and the distance between the obstacle and the vehicle can be directly calculated if the actual height of the object and the pixels on the image are known through the height ranging when no map element exists.
In this embodiment, after the step of confirming whether the height information of the obstacle is known, the method further includes:
s5, if the height information of the obstacle is unknown, judging whether the obstacle in the image shot by the monocular camera is matched with the element on the identified high-precision map;
and S6, if the obstacle in the image shot by the monocular camera is matched with the identified element on the high-precision map, acquiring the distance between the obstacle and the vehicle based on the monocular distance measurement principle and the information of the high-precision map.
In this embodiment, after the step of determining whether the obstacle in the image shot by the monocular camera matches the identified element on the high-precision map, the method further includes:
s7, if the obstacle in the image shot by the monocular camera is not matched with all the elements on the identified high-precision map, further judging whether a lane line exists;
and S8, if the lane line exists, calculating the distance between the obstacle and the vehicle through the lane line.
In this embodiment, the step of calculating the distance between the obstacle and the vehicle through the lane line specifically includes:
the width of the lane is obtained from the high-precision map, and then the distance of the obstacle and the distance between the obstacle and the vehicle are calculated through the pixel points of the lane in the image, the width of the lane, the camera parameters of the monocular camera and the height pixels of the obstacle in the image.
In this embodiment, after the step of determining whether the lane line exists, the method further includes:
s9, if no lane line exists, judging whether a preset road element exists, wherein the preset road element is any one of a road marking, a crosswalk and a road rod;
s10, if the preset road elements exist, converting the perspective view into a top view through reverse perspective transformation, and then carrying out interpolation change to determine the distance between the lane line calculation obstacle and the vehicle.
Specifically, if the obstacle is on the lane, the intersection of the obstacle and the ground is made a line perpendicular to the lane line, as in fig. 2, the calculated obstacle-to-camera distance can be converted into the calculated point-to-camera distance. Assuming that the lane width of the lane is the same, the lane width is obtained by a high-precision map, and the height of the obstacle and the distance of the obstacle from the camera can be calculated by a similar triangle, as shown in fig. 3. The height of the obstacle can be optimised afterwards, assuming that the height of the obstacle is constant. Calculation of distance through similar triangles can be performed by the height of the obstacle when there is no road sign where the high-precision map can be matched.
The width of the current lane can be obtained from the map on the assumption that the two lane lines are parallel and have the same width, and then the distance and the height of the obstacle can be calculated through the pixel points of the lane in the image, the width of the lane, the internal parameters of the camera and the height pixels of the obstacle in the image. Wherein, the obstacle is projected to the lane line, and according to the similar triangle, the projection point on the pixel is set B, P 'and the X' is known through the small hole imaging model. X can be obtained from a map, the focal length is known, and the distance Z between the obstacle and the vehicle can be calculated.
If the obstacle is an element on the high-precision map, the original size of the obstacle can be obtained directly through the high-precision map and the distance between the obstacle and the high-precision map can be obtained through the camera projection principle
If the obstacle is on the crosswalk/lane mark line, the obstacle can be obtained accurately through a high-precision map, the perspective view is converted into a top view through reverse perspective transformation, and then interpolation change is carried out to determine the distance between the lane line and the vehicle, wherein the distance between the obstacle and the vehicle is calculated.
Taking a road rod as an example, the actual distance from the road rod to the camera is known, and the distance from the road rod to the camera and the distance from the obstacle to the camera on the image after the back projection transformation are known, so that the distance between the obstacle and the vehicle can be calculated.
In summary, according to the system for measuring the distance between the obstacle based on the high-precision map and the monocular camera provided by the embodiment, firstly, the elements on the high-precision map are identified, then, the image shot by the monocular camera on the vehicle is acquired, and the obstacle in the image shot by the monocular camera and the identified elements on the high-precision map are subjected to matching analysis.
Referring to fig. 4, another embodiment of the present invention provides a system for measuring an obstacle distance based on a high-precision map and a monocular camera, the system comprising:
the identification module is used for identifying the elements on the high-precision map;
the acquisition module is used for acquiring an image shot by the monocular camera on the vehicle and carrying out matching analysis on the obstacle in the image shot by the monocular camera and the identified element on the high-precision map;
a first judging module for judging whether the height information of the obstacle is known;
the first calculation module is used for acquiring the distance between the obstacle and the vehicle based on the monocular ranging principle and the height information of the obstacle if the height information of the obstacle is known.
In this embodiment, the system further includes:
the second judging module is used for judging whether the obstacle in the image shot by the monocular camera is matched with the elements on the identified high-precision map or not if the height information of the obstacle is unknown;
and the second calculation module is used for acquiring the distance between the obstacle and the vehicle based on the monocular distance measurement principle and the information of the high-precision map if the obstacle in the image shot by the monocular camera is matched with the identified element on the high-precision map.
In this embodiment, the system further includes:
the third judging module is used for further judging whether a lane line exists or not if the obstacle in the image shot by the monocular camera is not matched with all the elements on the identified high-precision map;
and the third calculation module is used for calculating the distance between the obstacle and the vehicle through the lane line if the lane line exists.
In this embodiment, the third computing module is specifically configured to:
the width of the lane is obtained from the high-precision map, and then the distance of the obstacle and the distance between the obstacle and the vehicle are calculated through the pixel points of the lane in the image, the width of the lane, the camera parameters of the monocular camera and the height pixels of the obstacle in the image.
In this embodiment, the system further includes:
a fourth judging module, configured to judge whether a preset road element exists if no lane line exists, where the preset road element is any one of a road marking, a crosswalk, and a road rod;
and the fourth calculation module is used for converting the perspective view into a top view through reverse perspective transformation if the preset road element exists, and then determining the distance between the lane line calculation obstacle and the vehicle through interpolation change.
According to the system for measuring the distance between the obstacle based on the high-precision map and the monocular camera, provided by the embodiment, the elements on the high-precision map are firstly identified, then the image shot by the monocular camera on the vehicle is acquired, the obstacle in the image shot by the monocular camera and the identified elements on the high-precision map are subjected to matching analysis, if the height information of the obstacle is known, the distance between the obstacle and the vehicle can be directly acquired based on the monocular distance measurement principle and the height information of the obstacle, and the method and the device can directly measure the distance between the obstacle and the vehicle without using the monocular camera or knowing the size and the direction of the obstacle.
Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program is printed, as the program may be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.
It is to be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that: many changes, modifications, substitutions and variations may be made to the embodiments without departing from the spirit and principles of the invention, the scope of which is defined by the claims and their equivalents.
Claims (10)
1. A method for measuring obstacle distance based on a high-precision map and a monocular camera, comprising:
identifying elements on the high-precision map;
acquiring an image shot by a monocular camera on a vehicle, and carrying out matching analysis on an obstacle in the image shot by the monocular camera and the identified element on the high-precision map;
judging whether the height information of the obstacle is known;
if the height information of the obstacle is known, the distance between the obstacle and the vehicle is acquired based on the monocular ranging principle and the height information of the obstacle.
2. The method for measuring a distance of an obstacle based on a high-precision map and a monocular camera according to claim 1, wherein after the step of confirming whether the height information of the obstacle is known, the method further comprises:
if the height information of the obstacle is unknown, judging whether the obstacle in the image shot by the monocular camera is matched with the identified element on the high-precision map;
if an obstacle in an image shot by the monocular camera is matched with an element on the identified high-precision map, acquiring the distance between the obstacle and the vehicle based on the monocular distance measurement principle and the information of the high-precision map.
3. The method for measuring the obstacle distance based on the high-precision map and the monocular camera according to claim 2, wherein after the step of determining whether the obstacle in the image photographed by the monocular camera matches the element on the identified high-precision map, the method further comprises:
if the obstacle in the image shot by the monocular camera is not matched with all the elements on the identified high-precision map, further judging whether a lane line exists or not;
if a lane line exists, calculating the distance between the obstacle and the vehicle through the lane line.
4. A method for measuring obstacle distance based on a high-precision map and a monocular camera according to claim 3, wherein the step of calculating the distance between the obstacle and the vehicle by means of a lane line comprises:
the width of the lane is obtained from the high-precision map, and then the distance of the obstacle and the distance between the obstacle and the vehicle are calculated through the pixel points of the lane in the image, the width of the lane, the camera parameters of the monocular camera and the height pixels of the obstacle in the image.
5. The method for measuring obstacle distance based on a high-precision map and a monocular camera according to claim 3, wherein after the step of determining whether a lane line exists, the method further comprises:
if the lane line does not exist, judging whether a preset road element exists, wherein the preset road element is any one of a road marking, a crosswalk and a road rod;
if the preset road elements exist, converting the perspective view into a top view through reverse perspective transformation, and then carrying out interpolation change to determine the distance between the lane line calculation obstacle and the vehicle.
6. A system for measuring obstacle distance based on a high-precision map and a monocular camera, comprising:
the identification module is used for identifying the elements on the high-precision map;
the acquisition module is used for acquiring an image shot by the monocular camera on the vehicle and carrying out matching analysis on the obstacle in the image shot by the monocular camera and the identified element on the high-precision map;
a first judging module for judging whether the height information of the obstacle is known;
the first calculation module is used for acquiring the distance between the obstacle and the vehicle based on the monocular ranging principle and the height information of the obstacle if the height information of the obstacle is known.
7. The high-precision map and monocular camera based obstacle distance measuring system of claim 6, further comprising:
the second judging module is used for judging whether the obstacle in the image shot by the monocular camera is matched with the elements on the identified high-precision map or not if the height information of the obstacle is unknown;
and the second calculation module is used for acquiring the distance between the obstacle and the vehicle based on the monocular distance measurement principle and the information of the high-precision map if the obstacle in the image shot by the monocular camera is matched with the identified element on the high-precision map.
8. The high-precision map and monocular camera based obstacle distance measuring system of claim 7, further comprising:
the third judging module is used for further judging whether a lane line exists or not if the obstacle in the image shot by the monocular camera is not matched with all the elements on the identified high-precision map;
and the third calculation module is used for calculating the distance between the obstacle and the vehicle through the lane line if the lane line exists.
9. The method for measuring obstacle distance based on a high-precision map and a monocular camera according to claim 8, wherein the third calculation module is specifically configured to:
the width of the lane is obtained from the high-precision map, and then the distance of the obstacle and the distance between the obstacle and the vehicle are calculated through the pixel points of the lane in the image, the width of the lane, the camera parameters of the monocular camera and the height pixels of the obstacle in the image.
10. The high-precision map and monocular camera based obstacle distance measuring system of claim 8, further comprising:
a fourth judging module, configured to judge whether a preset road element exists if no lane line exists, where the preset road element is any one of a road marking, a crosswalk, and a road rod;
and the fourth calculation module is used for converting the perspective view into a top view through reverse perspective transformation if the preset road element exists, and then determining the distance between the lane line calculation obstacle and the vehicle through interpolation change.
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| CN (1) | CN116386000A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116953680A (en) * | 2023-09-15 | 2023-10-27 | 成都中轨轨道设备有限公司 | Image-based real-time ranging method and system for target object |
| CN117058210A (en) * | 2023-10-11 | 2023-11-14 | 比亚迪股份有限公司 | Distance calculation method and device based on vehicle-mounted sensor, storage medium and vehicle |
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2023
- 2023-02-23 CN CN202310159114.XA patent/CN116386000A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116953680A (en) * | 2023-09-15 | 2023-10-27 | 成都中轨轨道设备有限公司 | Image-based real-time ranging method and system for target object |
| CN116953680B (en) * | 2023-09-15 | 2023-11-24 | 成都中轨轨道设备有限公司 | Image-based real-time ranging method and system for target object |
| CN117058210A (en) * | 2023-10-11 | 2023-11-14 | 比亚迪股份有限公司 | Distance calculation method and device based on vehicle-mounted sensor, storage medium and vehicle |
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