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8 June 2012 Human actions recognition using bag of optical flow words
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Proceedings Volume 8334, Fourth International Conference on Digital Image Processing (ICDIP 2012); 833420 (2012) https://doi.org/10.1117/12.954130
Event: Fourth International Conference on Digital Image Processing (ICDIP 2012), 2012, Kuala Lumpur, Malaysia
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.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xu Zhang, Zhenjiang Miao, and Lili Wan "Human actions recognition using bag of optical flow words", Proc. SPIE 8334, Fourth International Conference on Digital Image Processing (ICDIP 2012), 833420 (8 June 2012); https://doi.org/10.1117/12.954130
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