Research Advanced in The Current State of Gait Recognition Based on Deep Learning

Abstract

Gait recognition is aimed to authenticate individuals through check their unique walking patterns. It has gradually become a popular research task in the computer vision community in recent years. Gait recognition has the advantages of non-intrusive, contactless and anti-spoofing compared to traditional human authentication methods, and has been widely used in many fields, such as supporting security systems, helping medical diagnosis and improving elderly care. Because of the rapid development of deep learning technology, the accuracy and speed of gait recognition have continuously made breakthroughs, and the modality of applicable research data has also expanded from 2D images to 3D point clouds. Focusing on the latest research progress in gait recognition, this paper provides an overview of image-based and point cloud-based gait recognition frameworks respectively, emphasizing their advantages and limitations. This paper also introduces representative gait recognition methods and their basic steps, such as OpenGait, which utilizes Lidargait point clouds to improve accuracy. We believe that the work in this paper can open a window for readers to gain a basic understanding of gait recognition and inspire further research in gait recognition.