This work targets people identification in video based on the way they walk (ie gait). While
classical methods typically derive gait signatures from sequences of binary silhouettes, in …

People identification in video based on the way they walk (ie, gait) is a relevant task in
computer vision using a noninvasive approach. Standard and current approaches typically …

This work targets people identification in video based on the way they walk (ie gait) by using
deep learning architectures. We explore the use of convolutional neural networks (CNN) for …

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 task of identifying people by the way they walk is known asgait recognition'. Although
gait is mainly used for identification, additional tasks as gender recognition or age estimation …

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 …

The goal of this paper is to evaluate how the fusion of multimodal features (ie, audio, RGB
and depth) can help in the challenging task of people identification based on their gait (ie …

Recognizing people by the way they walk-also known as gait recognition-has been studied
extensively in the recent past. Recent gait recognition methods solely focus on data …

Human gait or walking manner is a biometric feature that allows identification of a person
when other biometric features such as the face or iris are not visible. In this study, the …

In this work we investigate the problem of people recognition by their gait. For this task, we
implement deep learning approach using the optical flow as the main source of motion …