Complex Background Modeling and Motion Detection based on Texture Pattern Flow
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Gao, Y
Zhong, B
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Tampa, Florida, USA
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Abstract
This paper proposes a novel Texture Pattern Flow (TPF) for complex background modeling and motion detection. The Pattern Flow is proposed to encode the binary pattern changes among the neighborhoods in the space-time domain. To model the distribution of the TPF, the TPF integral histograms are used to extract the discriminative features to represent the input video. Experimental results on the public videos testify the effectiveness of the proposed method in comparison to LBP and GMM based background modeling methods.
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Proceedings - International Conference on Pattern Recognition
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