Body-part Segmentation for a Real Human Wearing Multiple-Colored Suit by a Mean Shift Based Algorithm(Internationa Session 5)
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概要
- 論文の詳細を見る
In this paper, we present a framework of body-part segmentation for a real human wearing multiple-colored suit, which has different colors for individual body parts. The segmentation framework would be very useful for estimating postures of a real human. Our work firstly runs a robust background modeling and detection method called codebook so that the human area is extracted from the background. Then, we apply the mean shift segmentation as well as edge detection to the extracted human area. Experimental results show that the proposed method achieves better performances than conventional segmentation methods.
- 社団法人電子情報通信学会の論文
- 2007-10-18
著者
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OHYA Jun
Graduate School of Global Information and Telecommunication and Studies, Waseda University
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Okazaki Jun
Graduate School Of Global Information And Telecommunication Studies Waseda University
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Guo Huimin
Graduate School of Global Information and Telecommunication Studies Waseda University
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Kang Dong-Wan
Graduate School of Global Information and Telecommunication Studies Waseda University
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Ohya Jun
Graduate School Of Global Information And Telecommunication And Studies Waseda University
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