Presentation 2017-05-26
Background Modeling based on Gaussian Mixture Model using Spatial Features
Kan Zheng, Toshio Kondo, Yuki Fukazawa, Takahiro Sasaki,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Many methods for detecting a moving object from surveillance video using a background model have been proposed. Mixed Gaussian distribution is widely used to construct background models, but it can not cope well with scenes due to the frequent background changes. In this paper, we proposed a method with high followability to background change by using spatial information of pixels as feature, constructing a background model with mixed Gaussian distribution at multilevel. The results of the proposed method were compared with the Ground Truth of the data set and evaluated by the F - measure method, and it was confirmed that the precision rate and the recall rate of the proposed method exceed the conventional methods such as Gaussian Mixture Model (GMM) and Local Binary Pattern (LBP).
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Background model / Moving object detection / Gaussian Mixture Model / Spatial information
Paper # SIP2017-24,IE2017-24,PRMU2017-24,MI2017-24
Date of Issue 2017-05-18 (SIP, IE, PRMU, MI)

Conference Information
Committee PRMU / IE / MI / SIP
Conference Date 2017/5/25(2days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Eisaku Maeda(NTT) / Seishi Takamura(NTT) / Yoshitaka Masutani(Hiroshima City Univ.) / Makoto Nakashizuka(Chiba Inst. of Tech.)
Vice Chair Seiichi Uchida(Kyushu Univ.) / Hironobu Fujiyoshi(Chubu Univ.) / Takayuki Hamamoto(Tokyo Univ. of Science) / Atsuro Ichigaya(NHK) / Yoshiki Kawata(Tokushima Univ.) / Yuichi Kimura(Kinki Univ.) / Masahiro Okuda(Univ. of Kitakyushu) / Shogo Muramatsu(Niigata Univ.)
Secretary Seiichi Uchida(Kyoto Univ.) / Hironobu Fujiyoshi(NTT) / Takayuki Hamamoto(NTT) / Atsuro Ichigaya(Chiba Inst. of Tech.) / Yoshiki Kawata(Aichi Inst. of Tech.) / Yuichi Kimura(Nagoya Inst. of Tech.) / Masahiro Okuda(Ritsumeikan Univ.) / Shogo Muramatsu(Chiba Inst. of Tech.)
Assistant Masaki Oonishi(AIST) / Takuya Funatomi(NAIST) / Kei Kawamura(KDDI R&D Labs.) / Keita Takahashi(Nagoya Univ.) / Ryo Haraguchi(Univ. of Hyogo) / Yasushi Hirano(Yamaguchi Univ.) / Osamu Watanabe(Takushoku Univ.)

Paper Information
Registration To Technical Committee on Pattern Recognition and Media Understanding / Technical Committee on Image Engineering / Technical Committee on Medical Imaging / Technical Committee on Signal Processing
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Background Modeling based on Gaussian Mixture Model using Spatial Features
Sub Title (in English)
Keyword(1) Background model
Keyword(2) Moving object detection
Keyword(3) Gaussian Mixture Model
Keyword(4) Spatial information
1st Author's Name Kan Zheng
1st Author's Affiliation Mie University(Mie Univ.)
2nd Author's Name Toshio Kondo
2nd Author's Affiliation Mie University(Mie Univ.)
3rd Author's Name Yuki Fukazawa
3rd Author's Affiliation Mie University(Mie Univ.)
4th Author's Name Takahiro Sasaki
4th Author's Affiliation Mie University(Mie Univ.)
Date 2017-05-26
Paper # SIP2017-24,IE2017-24,PRMU2017-24,MI2017-24
Volume (vol) vol.117
Number (no) SIP-47,IE-48,PRMU-49,MI-50
Page pp.pp.125-130(SIP), pp.125-130(IE), pp.125-130(PRMU), pp.125-130(MI),
#Pages 6
Date of Issue 2017-05-18 (SIP, IE, PRMU, MI)