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- W2369875002 abstract "In this paper, we propose a novel framework for dynamical texture modeling based on chaos theory. Our method first extracts features from dynamical texutre and concatenate the features to a feature vector. A video is then represented by a feature matrix. The mean shift clustering algorithm is used to cluster the feature vector which achieves segmenting videos into different motion patterns. The earth mover s distance(EMD) is employed to compute the feature cluster similarities and classify the dynamic textures. Experimental results indicate that: 1) The segmentation algorithm can cluster different motion patterns in videos; 2) The feature vector proposed in this paper can effectively characterize the dynamical texture; 3) The proposed algorithm can classify dynamical texture accurately. In addition, the algorithm is robust to video noise." @default.
- W2369875002 created "2016-06-24" @default.
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- W2369875002 date "2014-01-01" @default.
- W2369875002 modified "2023-09-28" @default.
- W2369875002 title "Chaotic Features for Motion Pattern Segmentation and Dynamic Texture Classification" @default.
- W2369875002 hasPublicationYear "2014" @default.
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