Automatically understanding human actions from video sequences is a very challenging problem. This involves the extraction of relevant visual information from a video sequence, re...
In this paper a novel method for view independent human movement representation and recognition, exploiting the rich information contained in multi-view videos, is proposed. The bi...
Nikolaos Gkalelis, Nikos Nikolaidis, Ioannis Pitas
The paper introduces an action recognition framework that uses concepts from the theory of chaotic systems to model and analyze nonlinear dynamics of human actions. Trajectories o...
We present a new method of computing invariants in videos captured from different views to achieve view-invariant action recognition. To avoid the constraints of collinearity or c...
Analysis of human perception of motion shows that information for representing the motion is obtained from the dramatic changes in the speed and direction of the trajectory. In thi...