Computer vision is one of the crucial fields in computer science. Depth sensors play the main role in human system kinematic analysis because of the gait features used in many application areas. Analyzing static and dynamic features of skeletal human body plays an important role in recognizing abnormal gait such as pathological gaits and neurological diseases gait. The main aim of this article is to extract human skeletal joint static features trajectories and model them in a mathematical form to distinguish between normal and hemiplegic gait. Each joint trajectory represents the locations of that joint over all the video frames. Two trajectories have been computed. These trajectories represent the distance between the two feet and walking point represent the Ground Central Walking Point (GCWP). The result shows that the leg with circular swing has a large distance in its trajectory.
Volume 11 | 10-Special Issue
Pages: 760-766
DOI: 10.5373/JARDCS/V11SP10/20192867