Presentation 2011-02-18
Probabilistic Background Texture Modeling for Object Detection
Satoshi YOSHINAGA, Atsushi SHIMADA, Hajime NAGAHARA, Rin-ichiro TANIGUCHI,
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Abstract(in English) We propose a new method of background modeling, which is considering the background texture, to detect objects. Many background models have been previously proposed, and they are divided into two types : "pixel-based models" which model stochastic changes in the value of each pixel and "spatial-based models" which model a local texture around each pixel. Pixel-based models cannot adapt to sudden change of pixel value caused by sudden illumination change and so on. On the contrary, spatial-based models cannot deal with texture changes such as a movement of clouds, trees, etc. To solve these problems, we propose a new probabilistic background model using local futures based on textures of the background.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Adaptive background model / Background Subtraction / Illumination change / Gaussian Mixture Model / Radial Reach Filter
Paper # PRMU2010-232
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Conference Information
Committee PRMU
Conference Date 2011/2/10(1days)
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Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Probabilistic Background Texture Modeling for Object Detection
Sub Title (in English)
Keyword(1) Adaptive background model
Keyword(2) Background Subtraction
Keyword(3) Illumination change
Keyword(4) Gaussian Mixture Model
Keyword(5) Radial Reach Filter
1st Author's Name Satoshi YOSHINAGA
1st Author's Affiliation Department of Advanced Information Technology, Kyushu University()
2nd Author's Name Atsushi SHIMADA
2nd Author's Affiliation Department of Advanced Information Technology, Kyushu University
3rd Author's Name Hajime NAGAHARA
3rd Author's Affiliation Department of Advanced Information Technology, Kyushu University
4th Author's Name Rin-ichiro TANIGUCHI
4th Author's Affiliation Department of Advanced Information Technology, Kyushu University
Date 2011-02-18
Paper # PRMU2010-232
Volume (vol) vol.110
Number (no) 414
Page pp.pp.-
#Pages 6
Date of Issue