Batch-incremental and robust principle component analysis (パターン認識・メディア理解)
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概要
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Incremental principle component analysis (IPCA) has been of great interest in computer vision and machine learning. In this paper, we introduce a new IPCA method, and extend it to robust PCA. The proposed method can keep an accurate track of the mean of the data, and can deal with a set of new observed data in batch each time in subspace updating. Furthermore, a weighting function can be simply incorporated in the proposed method. The performance of our method is illustrated in two experiments on face modeling and background modeling.
- 2011-01-13
著者
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Duan Guifang
Graduate School Of Engeneering And Science Ritsumeikan University
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Chen Yen-wei
College Of Information And Science Ristumeikan University
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Chen Yen-wei
College Of Information And Science Ritsumeikan University
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DUAN Guifang
University Research Organization of Science and Engineering, Ritsumeikan University
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Duan Guifang
University Research Organization Of Science And Engineering Ritsumeikan University
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