Decomposition of Dynamic Textures Using Morphological Component Analysis
The research context of this paper is dynamic texture analysis and characterization. Many dynamic textures can be modeled as large scale propagating wavefronts and local oscillating phenomena. After introducing a formal model for dynamic textures, the morphological component analysis (MCA) approach...
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Veröffentlicht in: | IEEE transactions on circuits and systems for video technology 2012-02, Vol.22 (2), p.188-201 |
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description | The research context of this paper is dynamic texture analysis and characterization. Many dynamic textures can be modeled as large scale propagating wavefronts and local oscillating phenomena. After introducing a formal model for dynamic textures, the morphological component analysis (MCA) approach with a well-chosen dictionary is used to retrieve the components of dynamic textures. We define two new strategies for adaptive thresholding in the MCA framework, which greatly reduce the computation time when applied on videos. Tests on real image sequences illustrate the efficiency of the proposed method. An application to global motion estimation is proposed and future prospects are finally exposed. |
doi_str_mv | 10.1109/TCSVT.2011.2159430 |
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Many dynamic textures can be modeled as large scale propagating wavefronts and local oscillating phenomena. After introducing a formal model for dynamic textures, the morphological component analysis (MCA) approach with a well-chosen dictionary is used to retrieve the components of dynamic textures. We define two new strategies for adaptive thresholding in the MCA framework, which greatly reduce the computation time when applied on videos. Tests on real image sequences illustrate the efficiency of the proposed method. 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Many dynamic textures can be modeled as large scale propagating wavefronts and local oscillating phenomena. After introducing a formal model for dynamic textures, the morphological component analysis (MCA) approach with a well-chosen dictionary is used to retrieve the components of dynamic textures. We define two new strategies for adaptive thresholding in the MCA framework, which greatly reduce the computation time when applied on videos. Tests on real image sequences illustrate the efficiency of the proposed method. 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subjects | Adaptation model Applied sciences Computer Science Detection, estimation, filtering, equalization, prediction Dictionaries Dynamic textures Dynamics Engineering Sciences Exact sciences and technology Heuristic algorithms Image processing Image sequences Information, signal and communications theory morphological component analysis (MCA) Signal and communications theory Signal and Image processing Signal processing Signal, noise spatio-temporal decompositions Telecommunications and information theory Transforms Videos |
title | Decomposition of Dynamic Textures Using Morphological Component Analysis |
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