Vehicle detection method based on monocular vision and laser radar fusion

Abstract

The invention relates to a vehicle detection method based on monocular vision and laser radar fusion. The method comprises the following steps of S1, obtaining an image feature map; S2, obtaining a point cloud feature map; S3, respectively extracting a point cloud feature vector flidar and an image feature vector fRGB from the point cloud feature map and the image feature map; S4, performing feature fusion on the point cloud feature vector flidar and the image feature vector fRGB to obtain a fusion feature fL; S5, obtaining a 3D bounding box of the vehicle according to the fusion feature fL, and obtaining corresponding category parameters; S6, removing the overlapped 3D bounding boxes to obtain the final 3D bounding boxes to complete vehicle detection. Compared with the prior art, the method has the advantages that the problems that the position of the vehicle is difficult to effectively estimate through monocular vision and missing detection is possibly caused by laser radar due to long-distance point cloud sparseness are solved, and the three-dimensional target detection effect on the vehicle is further improved.

Description

technical field [0001] The invention relates to the field of autonomous driving environment perception, in particular to a vehicle detection method based on fusion of monocular vision and laser radar. Background technique [0002] Vehicle detection is an essential part of the autonomous driving environment perception system, and target detection is also a basic problem in computer vision. Although researchers have made tremendous progress in this field in recent years, it is still a major challenge to develop a high-accuracy, high-efficiency, high-robust object detection system that can be used for autonomous driving. The detection of the vehicle is realized through 3D target detection. The output of the 3D target detection is a 3D bounding box, which contains the position and attitude information of the target vehicle in the 3D environment. With this information, the automatic driving decision-making system can make further driving decisions. , which is more important for ...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a vehicle detection method based on the fusion of monocular vision and laser radar in order to overcome the defects of the above-mentioned prior art, which helps to solve the problem that monocular vision is difficult to effectively estimate the vehicle position and laser radar may be due to The problem of missed detection caused by sparse long-distance point clouds further improves the effect of 3D target detection on vehicles

Images