Human Gait Recognition using LiDAR and Deep Learning Technologies

被引：3

作者：

Chiu, Tzu-Chun ^{[1
]}

Chen, Tzung-Shi ^{[1
]}

Lin, Jing-Mei ^{[1
]}

机构：

[1] Natl Univ Tainan, Dept Comput Sci & Informat Engn, Tainan, Taiwan

来源：

2022 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS - TAIWAN, IEEE ICCE-TW 2022 | 2022年

关键词：

Deep Learning; Gait Recognition; LiDAR; Long Short-Term Memory; Temporal Convolutional Network; NETWORKS;

D O I：

10.1109/ICCE-TAIWAN55306.2022.9869258

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This paper presents a system using Light Detection and Ranging (LiDAR) to sense the human gait, and training several deep learning models for gait recognition through the collected point cloud. Since the behavior of the human body is a continuous action, we choose deep learning architectures which deal with time-series data, Long Short-Term Memory (LSTM), Temporal Convolutional Network (TCN) and make the appropriate architecture combination to improve the accuracy of recognizing human gait.

引用

页码：43 / 44

页数：2

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