Journal of Applied Mathematics
Volume 2013 (2013), Article ID 605469, 9 pages
Research Article

Action Recognition by Joint Spatial-Temporal Motion Feature

1School of Computer Science, Sichuan University, Chengdu 610065, China
2College of Information Science and Technology, Chengdu University, Chengdu 610106, China

Received 4 March 2013; Accepted 28 April 2013

Academic Editor: Xiaoyu Song

Copyright © 2013 Weihua Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper introduces a method for human action recognition based on optical flow motion features extraction. Automatic spatial and temporal alignments are combined together in order to encourage the temporal consistence on each action by an enhanced dynamic time warping (DTW) algorithm. At the same time, a fast method based on coarse-to-fine DTW constraint to improve computational performance without reducing accuracy is induced. The main contributions of this study include (1) a joint spatial-temporal multiresolution optical flow computation method which can keep encoding more informative motion information than recent proposed methods, (2) an enhanced DTW method to improve temporal consistence of motion in action recognition, and (3) coarse-to-fine DTW constraint on motion features pyramids to speed up recognition performance. Using this method, high recognition accuracy is achieved on different action databases like Weizmann database and KTH database.