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In this paper, a novel framework to explore the activity spatial-temporal interactions in complex video surveillance scenes is proposed. Firstly, low-level motion features are detected and quantized into words. The Hierarchical Dirichlet Processes model is then applied to automatically cluster low-level features into atomic activities. Afterwards, the dynamic behaviors of the activities are represented...
In this paper, a framework based on the topic model is proposed for dynamic scene analysis. Firstly, low-level motion features are detected and denoised. The residual low level feature is then mapped into visual words using a novel adaptive quantization method. The first level latent Dirichlet allocation(LDA) model is applied to automatically cluster visual words into atomic activities. Afterwards,...
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