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Proceedings Paper

Human actions recognition using bag of optical flow words
Author(s): Xu Zhang; Zhenjiang Miao; Lili Wan
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Paper Abstract

In this paper, we present an improved approach to recognize human action based on the BOW model and the pLSA model. We propose an improved feature with optical flow to build our bag of words. This feature is able to reduce the high dimension of the pure optical flow template and also has abundant motion information. Then, we use the topic model of pLSA (probabilistic Latent Semantic Analysis) to classify human actions in a special way. We find that the existing methods lead to some mismatching of words due to the k-means clustering approach. To reduce the probability of mismatching, we add the spatial information to each word and improve the training and testing approach. Our approach of recognition is tested on two datasets, the KTH datasets and WEIZMANN datasets. The result shows its good performance.

Paper Details

Date Published: 8 June 2012
PDF: 6 pages
Proc. SPIE 8334, Fourth International Conference on Digital Image Processing (ICDIP 2012), 833420 (8 June 2012); doi: 10.1117/12.954130
Show Author Affiliations
Xu Zhang, Beijing Jiaotong Univ. (China)
Zhenjiang Miao, Beijing Jiaotong Univ. (China)
Lili Wan, Beijing Jiaotong Univ. (China)


Published in SPIE Proceedings Vol. 8334:
Fourth International Conference on Digital Image Processing (ICDIP 2012)
Mohamed Othman; Sukumar Senthilkumar; Xie Yi, Editor(s)

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