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The Scientific World Journal
Volume 2014, Article ID 495071, 10 pages
Research Article

The Approach for Action Recognition Based on the Reconstructed Phase Spaces

School of Information Science and Engineering, Central South University, Hunan 410075, China

Received 1 July 2014; Accepted 11 September 2014; Published 10 November 2014

Academic Editor: Shifei Ding

Copyright © 2014 Hong-bin Tu and Li-min Xia. 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 presents a novel method of human action recognition, which is based on the reconstructed phase space. Firstly, the human body is divided into 15 key points, whose trajectory represents the human body behavior, and the modified particle filter is used to track these key points for self-occlusion. Secondly, we reconstruct the phase spaces for extracting more useful information from human action trajectories. Finally, we apply the semisupervised probability model and Bayes classified method for classification. Experiments are performed on the Weizmann, KTH, UCF sports, and our action dataset to test and evaluate the proposed method. The compare experiment results showed that the proposed method can achieve was more effective than compare methods.