Target detection method and device, electronic equipment and storage medium

A target detection and target technology, which is applied in the field of data processing, can solve problems such as inapplicability and slow point cloud feature extraction speed, and achieve the effect of ensuring accuracy and improving extraction speed

Pending Publication Date: 2021-12-07
BEIJING JINGDONG QIANSHITECHNOLOGY CO LTD
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  • Abstract
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  • Claims
  • Application Information

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

Method used

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  • Target detection method and device, electronic equipment and storage medium
  • Target detection method and device, electronic equipment and storage medium
  • Target detection method and device, electronic equipment and storage medium

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Experimental program
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Embodiment 1

[0042] figure 1 It is a flow chart of a target detection method provided in Embodiment 1 of the present invention. This embodiment is applicable to the situation of rapidly extracting point cloud features, especially suitable to the situation of combining voxelization and point cloud information to quickly and accurately extract point cloud features. The method can be executed by the target detection device provided by the embodiment of the present invention, the device can be realized by software and / or hardware, and the device can be integrated on an electronic device, and the electronic device can be integrated in an automatic driving vehicle.

[0043] see figure 1 , the method of the embodiment of the present invention specifically includes the following steps:

[0044] S110. Obtain the original point cloud and the voxel grid corresponding to the original point cloud, and match each original point in the original point cloud to the corresponding voxel unit in the voxel g...

Embodiment 2

[0058] figure 2 It is a flowchart of a target detection method provided in Embodiment 2 of the present invention. This embodiment is optimized on the basis of the above-mentioned technical solutions. In this embodiment, optionally, matching each original point in the original point cloud to the corresponding voxel unit in the voxel grid may specifically include: for each original point in the original point cloud, according to the original The position information of the point determines the corresponding voxel unit of the original point in the voxel grid; obtains the unit information of the voxel unit, assigns the original point to the voxel unit, and updates the unit information according to the point cloud information of the original point; The point cloud to be extracted is determined according to the size information of the voxel grid and the point cloud information in each voxel unit, which may specifically include: determining the point to be extracted according to th...

Embodiment 3

[0075] image 3 It is a flowchart of a target detection method provided in Embodiment 3 of the present invention. This embodiment is optimized on the basis of the above-mentioned technical solutions. In this embodiment, optionally, inputting the point cloud to be extracted into the trained point cloud feature extraction network may include: inputting the point cloud to be extracted into the trained point cloud for the point cloud to be extracted The first neural network for feature extraction for each point to be extracted; the feature extraction result output by the first neural network is input to the trained second neural network for compressing each feature extraction result on the target dimension, The target dimension includes the size information of the voxel grid in the target direction; correspondingly, according to the output result of the point cloud feature extraction network, the point cloud feature of the original point cloud can be obtained, which can include: ...

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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 ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S7/48G01S17/931
CPCG01S7/4802G01S17/931
Inventor 刘浩徐卓然白宇董博王丹许新玉
Owner BEIJING JINGDONG QIANSHITECHNOLOGY CO LTD
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