The fields of human activity analysis have recently begun to diversify. Many researchers
have taken much interest in develo** action recognition or action prediction methods. The …

Digitization of human motion using skeleton representations offers exciting possibilities for a
large number of applications but, at the same time, requires innovative techniques for their …

The gesture recognition using motion capture data and depth sensors has recently drawn
more attention in vision recognition. Currently most systems only classify dataset with a …

Motion capture data describe human movements in the form of spatio-temporal trajectories
of skeleton joints. Intelligent management of such complex data is a challenging task for …

Today, the number of available videos on the Internet is significantly increased. Content-
based video retrieval is used for finding the users' desired items among these big video …

Action and gesture recognition from motion capture and RGB-D camera sequences has
recently emerged as a renowned and challenging research topic. The current methods can …

In this paper, we propose an integrated action classification and regression learning
framework for the fine-grained human action quality assessment of RGB videos. On the …

Action recognition based on the 3D coordinates of body skeleton joints is an important topic
in computer vision applications and human robot interaction. At present, most 3D data are …

Sparse representation is widely used by different human activity recognition methods.
Although many sparse feature extraction algorithms have been proposed in the literature …

Recent days have stamped enormous upsurge about health awareness in society. Self
tutoring systems for supervising the performed exercises offer numerous advantages and …