Target detection method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention discloses a target detection method and device, electronic equipment and a storage medium. The method comprises: acquiring original point clouds and voxel grids corresponding to the original point clouds, matching original points in the original point clouds to corresponding voxel units in the voxel grids respectively, and storing point cloud information of the original points matched to the voxel units in each voxel unit; determining a to-be-extracted point cloud according to the size information of the voxel grid and the information of each point cloud in each voxel unit, and inputting the to-be-extracted point cloud into a trained point cloud feature extraction network; according to an output result of the point cloud feature extraction network, obtaining a point cloud feature of the original point cloud; and obtaining a target detection result of the to-be-detected target in the original point cloud according to the point cloud features. According to the technical scheme provided by the embodiment of the invention, the to-be-extracted point clouds containing the point cloud information in the voxel grids are taken as a whole for point cloud feature extraction, and the effect of quickly extracting the point cloud features is achieved.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of data processing, and in particular, to a target detection method, device, electronic equipment, and storage medium. Background technique [0002] In order to ensure the safety of vehicle driving, autonomous vehicles need to detect and identify obstacles that may hinder driving, so as to perform reasonable avoidance actions according to the types and states of different obstacles. [0003] Currently the most mature detection scheme in the field of autonomous driving is the Bird's-eye View (BEV) detection scheme of lidar point cloud (hereinafter referred to as point cloud). This detection scheme extracts features from 3D point cloud to obtain BEV The image data under the perspective, and then based on the image data, the object to be detected in the original point cloud is detected, and the object to be detected can be an obstacle. [0004] In the process of realizing the present ...

AI Technical Summary

Problems solved by technology

[0004] In the process of realizing the present invention, the inventors found the following technical problems in the prior art: when performing feature extraction on 3D point cloud, the existing feature extraction scheme has the problem of slow point cloud feature extraction speed, which cannot be automatically well applied in driving vehicles

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