In the digital world of today, global security issues have given rise to video surveillance
devices. Gait-based human recognition is an emerging behavioral biometric trait for …

Gait recognition has emerged as an attractive biometric technology for the identification of
people by analysing the way they walk. However, one of the main challenges of the …

We propose in this paper a novel model-based gait recognition method, PoseGait. Gait
recognition is a challenging and attractive task in biometrics. Early approaches to gait …

This paper describes the world's largest gait database with wide view variation, the “OU-ISIR
gait database, multi-view large population dataset (OU-MVLP)”, and its application to a …

This paper studies an approach to gait based human identification via similarity learning by
deep convolutional neural networks (CNNs). With a pretty small group of labeled multi-view …

This paper proposes a method of gait recognition using a convolutional neural network
(CNN). Inspired by the great successes of CNNs in image recognition tasks, we feed in the …

The performance of gait recognition can be adversely affected by many sources of variation
such as view angle, clothing, presence of and type of bag, posture, and occlusion, among …

In this work we present a deep convolutional neural network using 3D convolutions for Gait
Recognition in multiple views capturing spatio-temporal features. A special input format …

The goal of gait recognition is to identify a person from a distance based on their walking
style using a visual camera. However, the covariates such as a walk with carrying a bag and …

In this paper, we discuss input/output architectures for convolutional neural network (CNN)-
based cross-view gait recognition. For this purpose, we consider two aspects: verification …