Presentation | 2005-10-28 Robust Human Detection in a Complicated Background using Multiple Gaussian Mixture Skin Models Rei MOCHIKI, Yuichi UCHIYAMA, Kazuya UEKI, Jiro KATTO, Tetsunori KOBAYASHI, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | We propose a human detection method using multiple skin model. Firstly, we detect skin candidates by applying Gaussian Mixture Models of human skins to the whole image, where the models were achieved for various environments (indoor or outdoor, lighting or no-lighting) in advance. We then select the most suitable model having maximum likelihood for the skin candidates, and carry out human region detection. This paper also shows the effectiveness of the proposed method experimentally. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Gaussian Mixture Model / Human Detection / Skin Model |
Paper # | PRMU2005-99 |
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Committee | PRMU |
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Conference Date | 2005/10/21(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Pattern Recognition and Media Understanding (PRMU) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Robust Human Detection in a Complicated Background using Multiple Gaussian Mixture Skin Models |
Sub Title (in English) | |
Keyword(1) | Gaussian Mixture Model |
Keyword(2) | Human Detection |
Keyword(3) | Skin Model |
1st Author's Name | Rei MOCHIKI |
1st Author's Affiliation | Science and Engineering, Waseda University() |
2nd Author's Name | Yuichi UCHIYAMA |
2nd Author's Affiliation | Science and Engineering, Waseda University |
3rd Author's Name | Kazuya UEKI |
3rd Author's Affiliation | Science and Engineering, Waseda University |
4th Author's Name | Jiro KATTO |
4th Author's Affiliation | / |
5th Author's Name | Tetsunori KOBAYASHI |
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Date | 2005-10-28 |
Paper # | PRMU2005-99 |
Volume (vol) | vol.105 |
Number (no) | 375 |
Page | pp.pp.- |
#Pages | 6 |
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