Advances in Vision-Based Gait Recognition: From Handcrafted to Deep Learning

Overview

Journal Sensors (Basel)

Publisher MDPI

Specialty Biotechnology

Date 2022 Aug 12

PMID 35957239

Authors

Jashila Nair Mogan

Chin Poo Lee

Kian Ming Lim

Affiliations

Soon will be listed here.

Abstract

Identifying people's identity by using behavioral biometrics has attracted many researchers' attention in the biometrics industry. Gait is a behavioral trait, whereby an individual is identified based on their walking style. Over the years, gait recognition has been performed by using handcrafted approaches. However, due to several covariates' effects, the competence of the approach has been compromised. Deep learning is an emerging algorithm in the biometrics field, which has the capability to tackle the covariates and produce highly accurate results. In this paper, a comprehensive overview of the existing deep learning-based gait recognition approach is presented. In addition, a summary of the performance of the approach on different gait datasets is provided.

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