CN117635731A - Method for calibrating external parameters between camera and laser radar based on vanishing point method - Google Patents
Method for calibrating external parameters between camera and laser radar based on vanishing point method Download PDFInfo
- Publication number
- CN117635731A CN117635731A CN202311619517.4A CN202311619517A CN117635731A CN 117635731 A CN117635731 A CN 117635731A CN 202311619517 A CN202311619517 A CN 202311619517A CN 117635731 A CN117635731 A CN 117635731A
- Authority
- CN
- China
- Prior art keywords
- camera
- laser radar
- coordinate system
- point
- focal length
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 75
- 230000003287 optical effect Effects 0.000 claims abstract description 25
- 238000005457 optimization Methods 0.000 claims abstract description 4
- 238000012545 processing Methods 0.000 claims abstract description 4
- 239000011159 matrix material Substances 0.000 claims description 15
- 239000013598 vector Substances 0.000 claims description 15
- 238000009877 rendering Methods 0.000 claims description 5
- 230000008030 elimination Effects 0.000 claims description 2
- 238000003379 elimination reaction Methods 0.000 claims description 2
- 238000001514 detection method Methods 0.000 description 3
- 230000004927 fusion Effects 0.000 description 3
- 238000013507 mapping Methods 0.000 description 3
- 241001270131 Agaricus moelleri Species 0.000 description 1
- 238000012935 Averaging Methods 0.000 description 1
- 101100391182 Dictyostelium discoideum forI gene Proteins 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
Landscapes
- Optical Radar Systems And Details Thereof (AREA)
Abstract
The invention discloses a vanishing point method-based camera and laser radar external parameter calibration method, which comprises the following steps: s1, acquiring an optical image of a target reference object by using a camera, and acquiring laser point cloud data of the target reference object by using a laser radar; s2, solving a principal point and a focal length of the camera according to the optical image; s3, processing laser point cloud data according to the solved main point and focal length of the camera to obtain a laser radar projection image; s4, calibrating external parameters between the camera and the laser radar by using vanishing points of the optical image and the laser radar projection image to obtain an external parameter calibration result; s5, further optimizing the main point, the focal length and the external parameter calibration result of the camera through an iterative optimization method to obtain an optimized external parameter calibration result. The invention solves the problem of external parameter calibration between the camera and the laser radar in a scene without a calibration plate by using vanishing points, and improves the efficiency and accuracy of external parameter calibration between the laser radar and the camera.
Description
Technical Field
The invention relates to the technical field of computer vision, in particular to a vanishing point method-based external parameter calibration method between a camera and a laser radar.
Background
In sensor data fusion algorithms, a camera and a lidar are often combined. The camera has rich environmental information including color, texture and semantic information; the laser can provide accurate three-dimensional ranging information, and is widely applied to the mapping and obstacle detection industries. The data fusion of the two can not only obtain stable and accurate navigation positioning results, but also have strong environment information sensing capability, and are suitable for the unmanned field. At present, with the advent of high resolution lidar, data approaching or even higher than the image resolution enables fusion algorithms of two sensors at the data level, but the realization of this target requires high precision external parameter calibration results between the camera and the radar.
Therefore, how to provide an external parameter calibration method between a camera and a laser radar with wide application range, stability, reliability and high precision is a problem to be solved by those skilled in the art.
Disclosure of Invention
In view of the above, the invention provides a vanishing point method-based external parameter calibration method between a camera and a laser radar, which can effectively improve the accuracy of external parameter calibration results between the camera and the laser radar.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
a vanishing point method-based external parameter calibration method between a camera and a laser radar comprises the following steps:
s1, acquiring an optical image of a target reference object by using a camera, and acquiring laser point cloud data of the target reference object by using a laser radar;
s2, solving a principal point and a focal length of the camera according to the optical image;
s3, processing the laser point cloud data according to the solved principal point and focal length of the camera to obtain a laser radar projection image;
s4, calibrating the external parameters between the camera and the laser radar by using vanishing points of the optical image and the laser radar projection image, and obtaining an external parameter calibration result.
Further, after the step S4, the method further includes:
and S5, further optimizing the principal point, the focal length and the external parameter calibration result of the camera by an iterative optimization method to obtain an optimized external parameter calibration result.
Further, the specific content of step S2 includes:
s21, extracting characteristic straight lines from the optical image, selecting required characteristic straight lines and calculating corresponding vanishing points;
s22, solving the principal point and the focal length of the camera by using the calculated orthogonal vanishing points.
Further, in the step S22, the principal point and focal length solving method of the camera is as follows:
the principal point of the camera is denoted as p i ＝[m 0 n 0 1] T Which satisfies the following conditions:
wherein p is i M is the principal point of the camera 0 And m 1 The main point coordinate parameters of the camera are obtained; u and C are main line related parameter matrixes,C＝[-c 1 -c 2 … -c n ] T wherein a is j 、b j And c j The mathematical expression of the j-th principal line is a as the related parameter of the j-th principal line j m 0 +b j n 0 +c j ＝0,j＝1,2,…,n；
Specific:
in the method, in the process of the invention,and->To solve the coordinate values of two sets of orthogonal vanishing points corresponding to the j-th principal line, wherein one set of orthogonal vanishing points is +.>And->Another group of orthogonal vanishing points is->And->
The focal length of the camera is denoted as f= [ f x f y ]Which satisfies the following conditions:
wherein f x 、f y Is a camera focal length parameter.
Further, the step S3 specifically includes:
s31, performing two-dimensional projection on the laser point cloud data through a projective geometric pinhole model according to the solved principal point and focal length of the camera;
s32, redundant points are removed from the projected two-dimensional image points by using a two-dimensional rendering method under a three-dimensional scene, and a laser radar projection image is obtained.
Further, the step S4 includes:
s41, extracting characteristic straight lines from the laser radar projection image, selecting a group of orthogonal parallel lines corresponding to the optical image and calculating orthogonal vanishing points of the orthogonal parallel lines;
s42, solving external parameters between the camera and the laser radar according to the calculated orthogonal vanishing points;
s43, solving a plurality of external parameters according to the steps S41 and S42, and carrying out weighted average on the plurality of external parameters to obtain the external parameter calibration result after error elimination.
Further, the step S42 includes:
the rotation matrix between the camera and the laser radar is as follows:
wherein c is a camera coordinate system, l is a laser radar coordinate system, and w is a world coordinate system;a rotation matrix from the camera coordinate system to the lidar coordinate system; />A rotation matrix from the world coordinate system to the lidar coordinate system; />A rotation matrix for the camera coordinate system to the world coordinate system;
the rotation matrix of the world coordinate system to the camera coordinate system is:
wherein r is 1 、r 2 And r 3 Is thatIs satisfied with the following conditions:
r 3 ＝r 1 ×r 2
in the method, in the process of the invention,and->To solve for a corresponding set of orthogonal vanishing points for the dominant line, wherein +.> K c As an internal reference of the camera, the expression is:
the position vector between the camera and the laser radar is as follows:
in the method, in the process of the invention,for the camera coordinate system to the lidarA position vector of the coordinate system; />A position vector from the world coordinate system to the lidar coordinate system; />A position vector for the camera coordinate system to the world coordinate system; />And->Can be obtained directly by sine and cosine theorem.
Further, the step S5 includes:
s51, updating the laser radar projection image according to the external parameter calibration result, and reversely solving the principal point and the focal length of the camera by utilizing the updated laser radar projection image to obtain the optimized principal point and focal length of the camera;
s52, updating the laser radar projection image again by using the optimized principal point and focal length of the camera, and solving external parameters between the camera and the laser radar by using a vanishing point method;
s53, repeating the steps S51 and S52, and finally obtaining the optimized external parameter calibration result.
Compared with the prior art, the invention discloses a method for calibrating the external parameters between the camera and the laser radar based on the vanishing point method, which realizes the data layer connection between three-dimensional laser point cloud data and two-dimensional optical images by using the projection and rendering technology, and simultaneously realizes the rapid external parameter calibration between the laser and the camera by using the vanishing point mode in the projective geometry, thereby solving the external parameter calibration problem between the camera and the laser radar in a scene without a calibration plate, and effectively improving the speed and the accuracy of the external parameter calibration result between the camera and the laser radar.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of an external parameter calibration method between a camera and a laser radar based on vanishing point method.
Fig. 2 is a schematic flow chart of external parameter calibration between a camera and a laser radar provided by the invention.
FIG. 3 is a schematic flow chart of the method for optimizing the external parameter calibration result by using the iterative method.
Fig. 4 is a schematic diagram of a geometric structure for solving a vector between a camera and a lidar according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. 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.
The embodiment of the invention discloses a vanishing point method-based camera and laser radar external parameter calibration method, which is shown in the attached figure 1 and comprises the following steps:
s1, acquiring an optical image of a target reference object by using a camera, and acquiring laser point cloud data of the target reference object by using a laser radar.
Fixedly placing a laser radar and a camera which need to be calibrated with external parameters in the same scene with a geometric object, taking the geometric object as a target reference object, keeping the positions of the laser radar and the camera unchanged midway, and collecting an optical image of the target reference object by using the camera; the laser point cloud data of the target reference object is collected by the laser radar and is used for generating laser point cloud projection images subsequently, the collection time is 1-2 minutes, the condition that the superimposed multi-frame point cloud data has higher density is met, and the quality of the laser point cloud projection images is improved.
It should be noted that the target reference object should have rectangular characteristics, and the camera and the laser radar that need to perform calibration external parameters do not need to have a larger common view area, but need to have the same orthogonal parallel straight lines in the field of view, so as to conveniently obtain more accurate orthogonal vanishing points.
S2, solving a principal point and a focal length of a camera according to the optical image, wherein the specific calculation process is as follows:
s21, extracting characteristic straight lines from the optical image, selecting required characteristic straight lines and calculating corresponding vanishing points.
First, a characteristic straight line is extracted from an optical image acquired by a camera by using an LSD (Line Segment Detector, straight line segment detection algorithm), comprising the steps of:
(1) Performing Gaussian downsampling on an optical image acquired by a camera;
(2) Carrying out gray gradient solving on pixel points in the optical image to obtain gradient values and gradient directions of each point, marking the gradient values and gradient directions as g, and taking the normal vector directions of the gradients as pixel directions h;
(3) Obtaining an alternative linear domain through the pixel direction H, and solving the minimum circumscribed rectangle of the area and the main direction H of the circumscribed rectangle;
(4) If the minimum circumscribed rectangle is slender, the probability of the characteristic straight line to be detected is high, and then the difference value between the direction H of each pixel point in the rectangle and the main direction H of the rectangle is judged to carry out straight line detection.
And secondly, selecting two required orthogonal parallel lines with the same plane from the characteristic straight lines extracted by the LSD method, and calculating corresponding vanishing points.
It is noted that when the orthogonal parallel lines are manually selected, a straight line with long length, small pixel error and obvious edge is required to be selected.
S22, solving the principal point and focal length of the camera by using the calculated orthogonal vanishing points.
Specifically, the principal point of the camera is denoted as p i ＝[m 0 n 0 1] T Which satisfies the following conditions:
wherein p is i M is the principal point of the camera 0 And m 1 The main point coordinate parameters of the camera are obtained; u and C are main line related parameter matrixes,C＝[-c 1 -c 2 …-c n ] T wherein a is j 、b j And c j The mathematical expression of the j-th principal line is a as the related parameter of the j-th principal line j m 0 +b j n 0 +c j ＝0,j＝1,2,…,n；
Further:
in the method, in the process of the invention,and->To solve the coordinate values of two sets of orthogonal vanishing points corresponding to the j-th principal line, wherein one set of orthogonal vanishing points is +.>And->Another group of orthogonal vanishing points is->And->
The focal length of the camera is denoted as f= [ f x f y ]Which satisfies the following conditions:
wherein f x 、f y Is a camera focal length parameter.
S3, processing laser point cloud data according to the solved principal point and focal length of the camera to obtain a laser radar projection image, wherein the specific contents include:
s31, performing two-dimensional projection on laser point cloud data through a projection geometry pinhole model according to the solved principal point and focal length of the camera.
The projected two-dimensional plane points are:
in the formula [ m n 1 ]] T Is two-dimensional Ping Miandian after projection; [ X ] l Y l Z l 1] T A three-dimensional laser spot before projection; r is R init And t init Respectively, any given initial value of external parameter, usuallyt init ＝[0 0 0]。
And performing traversal projection on all the collected laser point cloud data, so that mapping from three-dimensional points in space to two-dimensional points on a plane can be realized.
S32, redundant points are removed from the projected two-dimensional image points by using a two-dimensional rendering method under a three-dimensional scene, and a laser radar projection image is obtained.
After mapping is achieved, the existing two-dimensional projection points are removed and screened by using a two-dimensional rendering method Z-Buffer under the three-dimensional scene, namely, under the same two-dimensional coordinates, the points with larger depth are blocked by the points with smaller depth, and the points with larger depth are removed to reduce the operation amount. Generating gray scale corresponding to the two-dimensional position by the depth and the reflection intensity of the residual two-dimensional points, wherein the specific expression is as follows:
wherein w is depth The weight is occupied by the depth; d is the depth of the laser spot, I is the intensity of the laser spot; d, d max Is the maximum value of depth in the laser point cloud, I max Maximum intensity in the laser point cloud.
Gray scales are filled in the images with the same size, and laser radar projection images to be further processed are obtained.
S4, calibrating external parameters between the camera and the laser radar by using vanishing points of the optical image and the laser radar projection image.
Specifically, referring to fig. 2, the content of step S4 includes:
s41, extracting characteristic straight lines from the laser radar projection image, selecting a group of orthogonal parallel lines corresponding to the optical image, and calculating orthogonal vanishing points.
S42, solving external parameters between the camera and the laser radar according to the calculated orthogonal vanishing points.
Further, the rotation matrix between the camera and the lidar is:
wherein c is a camera coordinate system; l is a laser radar coordinate system; w is a world coordinate system, wherein the world coordinate system is a coordinate system formed by a selected straight line for solving vanishing points in reality;a rotation matrix from a camera coordinate system to a laser radar coordinate system;a rotation matrix from a world coordinate system to a laser radar coordinate system; />A rotation matrix from a camera coordinate system to a world coordinate system;
to solve forIs>For example, the rotation matrix to solve the world coordinate system to the camera coordinate system is:
wherein r is 1 、r 2 And r 3 Is thatIs satisfied with the following conditions:
r 3 ＝r 1 ×r 2
in the method, in the process of the invention,and->To solve for a corresponding set of orthogonal vanishing points for the dominant line, wherein +.> K c As an internal reference of the camera for projection, the expression is:
the position vector between the camera and the laser radar is:
in the method, in the process of the invention,position vectors from a camera coordinate system to a laser radar coordinate system; />Position vectors from the world coordinate system to the laser radar coordinate system; />Position vectors from a camera coordinate system to a world coordinate system; />And->Can be obtained directly by sine and cosine theorem.
To solve for a position vector from a camera coordinate system to a world coordinate systemFor example, referring to fig. 3, the geometric relationship between the camera coordinate system to the world coordinate system is:
wherein O is c For the origin of the camera coordinate system, O w Is the origin of the world coordinate system; o is the projection point of the world coordinate system on the image plane; b is selected to be O w The other end of the line.
According to the sine theorem:
wherein p is i Is the principal point of the camera;is O w Vanishing points in the B direction; b is the projection point of point B on the image plane.
According to the cosine law:
s43, solving a plurality of external parameters according to the steps S41 and S42, and carrying out weighted average on the plurality of external parameters to eliminate errors extracted by straight lines in single external parameter solving, so as to obtain an external parameter calibration result after the errors are eliminated.
Further, the weight used for weighted averaging is defined by triangle similarity and vanishing line slope as:
wherein w is 1 And w is equal to 2 Is the weight of triangle similarity, w 3 Is a slope weight; o (O) l The method comprises the steps of (1) setting a coordinate origin of a laser radar projection image; o (O) c Is the origin of coordinates of the optical image;and->Is a group of orthogonal vanishing points under a laser radar coordinate system>And->A group of orthogonal vanishing points in a camera coordinate system; /> And->A straight line formed by points; />The slope of the vanishing line of the projected image of the laser radar; />Is the slope of the vanishing line of the optical image.
S5, further optimizing the main point, the focal length and the external parameter calibration result of the camera through an iterative optimization method to obtain an optimized external parameter calibration result.
Specifically, referring to fig. 4, the content of step S5 includes:
and S51, updating the laser radar projection image according to the external parameter calibration result, and reversely solving the principal point and the focal length of the camera by utilizing the updated laser radar projection image to obtain the optimized principal point and the optimized focal length of the camera.
And S52, updating the laser radar projection image again by using the main point and the focal length of the optimized camera, and solving external parameters between the camera and the laser radar by using a vanishing point method.
S53, repeating the steps S51 and S52, and finally obtaining the optimized external parameter calibration result.
The external parameter calibration result with higher precision between the camera and the laser radar can be obtained based on the vanishing point method by sequentially executing the above processes.
It should be noted that, if simultaneous calibration of external parameters between multiple groups of cameras and lidar is to be performed simultaneously, only data of the same target reference object needs to be collected by using all the camera and lidar equipment groups in step S1, and similarly, all the cameras and lidar equipment groups needing to perform calibration of external parameters need to satisfy that the same orthogonal parallel lines exist in the field of view; and selecting corresponding orthogonal parallel lines in the step S4, and simultaneously solving external parameters between all cameras and the laser radar equipment group.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. A vanishing point method-based external parameter calibration method between a camera and a laser radar is characterized by comprising the following steps:
s1, acquiring an optical image of a target reference object by using a camera, and acquiring laser point cloud data of the target reference object by using a laser radar;
s2, solving a principal point and a focal length of the camera according to the optical image;
s3, processing the laser point cloud data according to the solved principal point and focal length of the camera to obtain a laser radar projection image;
s4, calibrating the external parameters between the camera and the laser radar by using vanishing points of the optical image and the laser radar projection image, and obtaining an external parameter calibration result.
2. The method for calibrating external parameters between a camera and a laser radar based on vanishing point method according to claim 1, wherein the step S4 further comprises:
and S5, further optimizing the principal point, the focal length and the external parameter calibration result of the camera by an iterative optimization method to obtain an optimized external parameter calibration result.
3. The method for calibrating external parameters between a camera and a laser radar based on vanishing point method according to claim 1, wherein the specific content of step S2 includes:
s21, extracting characteristic straight lines from the optical image, selecting required characteristic straight lines and calculating corresponding vanishing points;
s22, solving the principal point and the focal length of the camera by using the calculated orthogonal vanishing points.
4. The method for calibrating external parameters between a camera and a laser radar based on vanishing point method according to claim 3, wherein the method for solving principal point and focal length of the camera in step S22 is as follows:
the principal point of the camera is denoted as p i ＝[m 0 n 0 1] T Which satisfies the following conditions:
wherein p is i M is the principal point of the camera 0 And m 1 The main point coordinate parameters of the camera are obtained; u and C are main line related parameter matrixes,C＝[-c 1 -c 2 …-c n ] T wherein a is j 、b j And c j The mathematical expression of the j-th principal line is a as the related parameter of the j-th principal line j m 0 +b j n 0 +c j ＝0,j＝1,2,…,n；
Specific:
in the method, in the process of the invention,and->To solve the coordinate values of two sets of orthogonal vanishing points corresponding to the j-th principal line, wherein one set of orthogonal vanishing points is +.>And->Another group of orthogonal vanishing points is->And->
The focal length of the camera is denoted as f= [ f x f y ]Which satisfies the following conditions:
wherein f x 、f y Is a camera focal length parameter.
5. The method for calibrating external parameters between a camera and a laser radar based on vanishing point method according to claim 1, wherein the step S3 specifically includes:
s31, performing two-dimensional projection on the laser point cloud data through a projective geometric pinhole model according to the solved principal point and focal length of the camera;
s32, redundant points are removed from the projected two-dimensional image points by using a two-dimensional rendering method under a three-dimensional scene, and a laser radar projection image is obtained.
6. The method for calibrating external parameters between a camera and a laser radar based on vanishing point method according to claim 1, wherein the step S4 includes:
s41, extracting characteristic straight lines from the laser radar projection image, selecting a group of orthogonal parallel lines corresponding to the optical image and calculating orthogonal vanishing points of the orthogonal parallel lines;
s42, solving external parameters between the camera and the laser radar according to the calculated orthogonal vanishing points;
s43, solving a plurality of external parameters according to the steps S41 and S42, and carrying out weighted average on the plurality of external parameters to obtain the external parameter calibration result after error elimination.
7. The method for calibrating external parameters between a camera and a lidar according to claim 6, wherein the step S42 comprises:
the rotation matrix between the camera and the laser radar is as follows:
wherein c is a camera coordinate system, l is a laser radar coordinate system, and w is a world coordinate system;a rotation matrix from the camera coordinate system to the lidar coordinate system; />A rotation matrix from the world coordinate system to the lidar coordinate system;a rotation matrix for the camera coordinate system to the world coordinate system;
the rotation matrix of the world coordinate system to the camera coordinate system is:
wherein r is 1 、r 2 And r 3 Is thatIs satisfied with the following conditions:
r 3 ＝r 1 ×r 2
in the method, in the process of the invention,and->To solve for a corresponding set of orthogonal vanishing points for the dominant line, wherein +.> K c As an internal reference of the camera, the expression is:
the position vector between the camera and the laser radar is as follows:
in the method, in the process of the invention,a position vector from the camera coordinate system to the laser radar coordinate system; />A position vector from the world coordinate system to the lidar coordinate system; />A position vector for the camera coordinate system to the world coordinate system; />And->Can be obtained directly by sine and cosine theorem.
8. The method for calibrating external parameters between a camera and a laser radar based on vanishing point method according to claim 2, wherein the step S5 includes:
s51, updating the laser radar projection image according to the external parameter calibration result, and reversely solving the principal point and the focal length of the camera by utilizing the updated laser radar projection image to obtain the optimized principal point and focal length of the camera;
s52, updating the laser radar projection image again by using the optimized principal point and focal length of the camera, and solving external parameters between the camera and the laser radar by using a vanishing point method;
s53, repeating the steps S51 and S52, and finally obtaining the optimized external parameter calibration result.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311619517.4A CN117635731A (en) | 2023-11-30 | 2023-11-30 | Method for calibrating external parameters between camera and laser radar based on vanishing point method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311619517.4A CN117635731A (en) | 2023-11-30 | 2023-11-30 | Method for calibrating external parameters between camera and laser radar based on vanishing point method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117635731A true CN117635731A (en) | 2024-03-01 |
Family
ID=90033427
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311619517.4A Pending CN117635731A (en) | 2023-11-30 | 2023-11-30 | Method for calibrating external parameters between camera and laser radar based on vanishing point method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117635731A (en) |
-
2023
- 2023-11-30 CN CN202311619517.4A patent/CN117635731A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110135455B (en) | Image matching method, device and computer readable storage medium | |
| CN107316325B (en) | Airborne laser point cloud and image registration fusion method based on image registration | |
| US10580164B2 (en) | Automatic camera calibration | |
| WO2018127007A1 (en) | Depth image acquisition method and system | |
| CN107767440B (en) | Cultural relic sequence image fine three-dimensional reconstruction method based on triangulation network interpolation and constraint | |
| US8355565B1 (en) | Producing high quality depth maps | |
| CN111127422A (en) | Image annotation method, device, system and host | |
| CN111123242B (en) | Combined calibration method based on laser radar and camera and computer readable storage medium | |
| CN111862180B (en) | Camera set pose acquisition method and device, storage medium and electronic equipment | |
| CN112396640A (en) | Image registration method and device, electronic equipment and storage medium | |
| CN113205604A (en) | Feasible region detection method based on camera and laser radar | |
| CN113327296B (en) | Laser radar and camera online combined calibration method based on depth weighting | |
| CN116129037B (en) | Visual touch sensor, three-dimensional reconstruction method, system, equipment and storage medium thereof | |
| CN113506372A (en) | Environment reconstruction method and device | |
| CN111709995B (en) | Position calibration method between laser radar and camera | |
| CN114758005B (en) | Laser radar and camera external parameter calibration method and device | |
| CN113808103A (en) | Automatic road surface depression detection method and device based on image processing and storage medium | |
| CN112002016A (en) | Continuous curved surface reconstruction method, system and device based on binocular vision | |
| CN109902695B (en) | Line feature correction and purification method for image pair linear feature matching | |
| CN116402904A (en) | Combined calibration method based on laser radar inter-camera and monocular camera | |
| CN116246119A (en) | 3D target detection method, electronic device and storage medium | |
| CN117635731A (en) | Method for calibrating external parameters between camera and laser radar based on vanishing point method | |
| CN114782556A (en) | Camera and laser radar registration method, system and storage medium | |
| CN115409898A (en) | High-precision camera calibration method and device based on special annular calibration plate | |
| CN112270693B (en) | Method and device for detecting motion artifact of time-of-flight depth camera |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |