Long-tailed classification with fine-grained appearance, eg, in chest X-ray images, is very
challenging due to the very similar appearance and imbalanced distribution between normal …

To facilitate human gait recognition, this paper proposes a new frontal-view gait recognition
method using gait dynamics and deep learning. Rather than adopting lateral-view …

Gait recognition aims to obtain people's identity through body shape and walking posture.
Existing gait recognition studies focus on low vertical view recognition, in which the person …

Gait recognition is instrumental in crime prevention and social security, for it can be
conducted at a long distance without the cooperation of subjects. However, existing datasets …

Gait recognition plays an important role in video surveillance and security by identifying
humans based on their unique walking patterns. The existing gait recognition methods have …

View change causes significant differences in the gait appearance. Consequently,
recognizing gait in cross-view scenarios is highly challenging. Most recent approaches …

Gait recognition is an important biometric technology that allows for the remote collection of
stakeholders' characteristics, without requiring their explicit cooperation. It has gained …

Gait recognition enables the non-contact identification of individuals from a distance based
on their walking patterns and body shapes. For vision-based gait recognition, covariates (eg …

Despite that much progress has been reported in gait recognition, most of these existing
works adopt lateral-view parameters as gait features, which requires large area of data …

Gait recognition has attracted increasing attention from academia and industry as a human
recognition technology from a distance in non-intrusive ways without requiring cooperation …