Background Analysis of gait features provides important information during the treatment of
neurological disorders, including Parkinson's disease. It is also used to observe the effects …

Gait is a useful biometric feature for human identification in video surveillance applications
since it can be obtained without subject cooperation. In recent years, model-based gait …

The paper is a comprehensive study on classification of motion capture data on the basis of
dynamic time warping (DTW) transform. It presents both theoretical description of all applied …

Gait or walking pattern has been known as one of the alternative biometric solutions used in
surveillance monitoring and control. The methods of gait recognition have been developed …

Most contribution to the field of structure‐based human gait recognition has been done
through design of extraordinary gait features. Many research groups that address this topic …

Gait recognition from motion capture data, as a pattern classification discipline, can be
improved by the use of machine learning. This article contributes to the state of the art with a …

The model-based gait analysis of kinematic characteristics of the human body has been
used to identify individuals. To extract gait features, spatiotemporal changes of anatomical …

Analysis and recognition of motion patterns from data acquired by body-worn inertial
sensors is an emerging technology in sports. In this paper we propose an effective method …

This work offers a design of a video surveillance system based on a soft biometric-gait
identification from MoCap data. The main focus is on two substantial issues of the video …

In this study, a framework for view‐invariant gait recognition on the basis of markerless
motion tracking and dynamic time warping (DTW) transform is presented. The system …