Human Extremity Extraction for Pose Representation Applications

Silhouette border’s extremities can be considered as describing features for human postures. Using of extremities for posture representation, and hence action recognition, is a simple and time efficient method that can also reduce the error rate. But unfortunately, popular extremity extraction methods e.g. star skeleton methods, encountered with enormous faults. In this paper, we propose a new method for extremity extraction with minimum error rate. First, we introduce curvature as a feature that can be used for extraction of candidate extremities. Since, the curvature is a boundary feature, it is insensitive to posture situations. Two filtering steps are then applied for minimizing wrong features. Experimental results demonstrate the privileged performance of the proposed algorithm to extract the extremities and so the human posture against the best reported works.

کلیدواژه ها:

Extremity extraction ، pose representation ، silhouette ، convexity