Human Gait Recognition using LiDAR and Deep Learning Technologies

Abstract

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.