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

Gait recognition is an essential biometric technique that recognizes humans at a distance
through their unique walking style. In the present era of deep learning, automated gait …

One-shot image semantic segmentation poses a challenging task of recognizing the object
regions from unseen categories with only one annotated example as supervision. In this …

Model-based gait recognition is considered to be promising due to the robustness against
some variations, such as clothing and baggage carried. Although model-based gait …

Recently, deep learning-based cross-view gait recognition has become popular owing to the
strong capacity of convolutional neural networks (CNNs). Current deep learning methods …

Gait recognition aims to recognize persons' identities by walking styles. Gait recognition has
unique advantages due to its characteristics of non-contact and long-distance compared …

Gait recognition is one of the most important techniques for human identification at a
distance. Most current gait recognition frameworks consist of several separate steps …

This paper describes a novel gait pattern recognition method based on Long Short-Term
Memory (LSTM) and Convolutional Neural Network (CNN) for lower limb exoskeleton. The …

As a biological feature that can be recognized from a distance, gait has a wide range of
applications such as crime prevention, judicial identification, and social security. However …

Gait recognition can be used in person identification and re-identification by itself or in
conjunction with other biometrics. Although gait has both spatial and temporal attributes, and …