Human Action Recognition Based on Template Matching

This paper presents a new method of human action recognition, which is based on R transform and template matching after the key frame is extracted from a cycle. For a key binary human silhouette, R transform is employed to represent low-level features. The advantage of the R transform lies in its low computational complexity and geometric invariance. We utilize a novel string matching scheme based on edit distance is proposed to analyze different human actions. Compared with other methods, ours is superior because the descriptor is robust to frame loss in the video sequence, disjoint silhouettes and holes in the shape, and thus achieves better performance in similar activities recognition, simple representation, computational complexity and template generalization. Sufficient experiments have proved the efficiency. (c) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [CEIS 2011]