Special Section on Video Surveillance and Transportation Imaging Applications

Position and locality constrained soft coding for human action recognition

[+] Author Affiliations
Bin Wang

National University of Defense Technology, College of Information System and Management, #109 Deya Road, Changsha, Hunan 410073, China

Yu Liu

National University of Defense Technology, College of Information System and Management, #109 Deya Road, Changsha, Hunan 410073, China

Wenhua Xiao

National University of Defense Technology, College of Information System and Management, #109 Deya Road, Changsha, Hunan 410073, China

Wei Xu

National University of Defense Technology, College of Information System and Management, #109 Deya Road, Changsha, Hunan 410073, China

Maojun Zhang

National University of Defense Technology, College of Information System and Management, #109 Deya Road, Changsha, Hunan 410073, China

J. Electron. Imaging. 22(4), 041118 (Oct 11, 2013). doi:10.1117/1.JEI.22.4.041118
History: Received April 1, 2013; Revised August 21, 2013; Accepted August 28, 2013
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Abstract.  Although the traditional bag-of-words model has shown promising results for human action recognition, in the feature coding phase, the ambiguous features from different body parts are still difficult to distinguish. Furthermore, it also suffers from serious representation error. We propose an innovative coding strategy called position and locality constrained soft coding (PLSC) to overcome these limitations. PLSC uses the feature position in a human oriented region of interest (ROI) to distinguish the ambiguous features. We first construct a subdictionary for each feature by selecting the bases from their spatial neighbor in human ROI. Then, a modified soft coding with locality constraint is adopted to alleviate the quantization error and preserve the manifold structure of features. This novel coding algorithm increases both the representation accuracy and discriminative power with low computational cost. The human action recognition experimental results on KTH, Weizmann, and UCF sports datasets show that PLSC can achieve a better performance than previous competing feature coding methods.

© 2013 SPIE and IS&T

Citation

Bin Wang ; Yu Liu ; Wenhua Xiao ; Wei Xu and Maojun Zhang
"Position and locality constrained soft coding for human action recognition", J. Electron. Imaging. 22(4), 041118 (Oct 11, 2013). ; http://dx.doi.org/10.1117/1.JEI.22.4.041118


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