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 …

Human gait is a periodic motion of body segments—the analysis of motion and related
studies is termed gait analysis. Gait Analysis has gained much popularity because of its …

Existing studies for gait recognition are dominated by 2D representations like the silhouette
or skeleton of the human body in constrained scenes. However, humans live and walk in the …

Gait benchmarks empower the research community to train and evaluate high-performance
gait recognition systems. Even though growing efforts have been devoted to cross-view …

Gait recognition, applied to identify individual walking patterns in a long-distance, is one of
the most promising video-based biometric technologies. At present, most gait recognition …

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 …

Gait, the walking pattern of individuals, is one of the most important biometrics modalities.
Most of the existing gait recognition methods take silhouettes or articulated body models as …

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 …

Current person re-identification (re-id) methods typically rely on single-frame imagery
features, and ignore space-time information from image sequences. Single-frame (single …

Person re-identification is an important task in video surveillance systems. It can be formally
defined as establishing the correspondence between images of a person taken from …