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 …

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 …

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 …

This paper presents a comprehensive exposition of deep learning architectures and
pipelines for biometric applications using complex characteristics of human gait. The variety …

In this paper, we proposed a gait type classification method based on deep learning using a
smart insole with various sensor arrays. We measured gait data using a pressure sensor …

Gait can be used to recognize people in an uncooperative and noninvasive manner and it is
hard to imitate or counterfeit, which makes it suitable for video surveillance. The current …

Human gait recognition has emerged as a branch of biometric identification in the last
decade, focusing on individuals based on several characteristics such as movement, time …

We face the problem of gait recognition by using a robust deep learning model based on
graphs. The proposed graph based learning approach, named Time based Graph Long …

Human gait is a proven biometric trait with applications in security for authentication and
disease diagnosis. However, it is one-sided to express and interpret gait data from a single …

Current gait recognition systems employ different types of manual attention mechanisms,
like horizontal cropping of the input data to guide the training process and extract useful gait …