Gait recognition is an appealing biometric modality which aims to identify individuals based
on the way they walk. Deep learning has reshaped the research landscape in this area …

In the recent past, deep learning methods have demonstrated remarkable success for
supervised learning tasks in multiple domains including computer vision, natural language …

Gait is one of the most promising biometrics that aims to identify pedestrians from their
walking patterns. However, prevailing methods are susceptible to confounders, resulting in …

Video-based gait recognition has achieved impressive results in constrained scenarios.
However, visual cameras neglect human 3D structure information, which limits the feasibility …

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 …

The scientific literature on automated gait analysis for human recognition has grown
dramatically over the past 15 years. A number of sensing modalities including those based …

Gait recognition is of great importance in the fields of surveillance and forensics to identify
human beings since gait is the unique biometric feature that can be perceived efficiently at a …

The essential human gait parameters are briefly reviewed, followed by a detailed review of
the state of the art in deep learning for the human gait analysis. The modalities for capturing …

Gait recognition aims to identify a person at a distance, serving as a promising solution for
long-distance and less-cooperation pedestrian recognition. Recently, significant advances …

This paper describes the world's largest gait database-the “OU-ISIR Gait Database, Large
Population Dataset”-and its application to a statistically reliable performance evaluation of …