Technology of Graphic & Image
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1200-1203

Pedestrian detection based on LiDAR data

Ren Kefei
Zhang Li
Dept. of Electronic Engineering, Tsinghua University, Beijing 100084, China

Abstract

Pedestrian detection is a task which is necessary among all tasks leveraged in automatic driving domain. Traditional pedestrian detection algorithms took fully advantage of image data, unable to obtain depth of objects. To address aforementioned issue, this paper proposed a method based on raw LiDAR point cloud data. The proposed method combined traditional moving object detection in LiDAR data and point cloud recognition by deep learning, and was capable of perception and pedestrian detection without images, obtaining 3D location of pedestrian, therefore helping central control system make reasonable decisions. This method experimented in 3D object detection task of KITTI dataset, obtained 33.37% AP(average precision) on moderate cases. The results show that the proposed method performs better than other algorithm based on LiDAR data, which hence indicates the effectiveness of proposed method.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.10.0786
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 4
Section: Technology of Graphic & Image
Pages: 1200-1203
Serial Number: 1001-3695(2020)04-052-1200-04

Publish History

[2020-04-05] Printed Article

Cite This Article

任科飞, 张利. 基于激光雷达数据的行人检测 [J]. 计算机应用研究, 2020, 37 (4): 1200-1203. (Ren Kefei, Zhang Li. Pedestrian detection based on LiDAR data [J]. Application Research of Computers, 2020, 37 (4): 1200-1203. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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