Presentation 2014/2/6
Background Modeling using Exponentially Weighted Histogram
Tsubasa MINEMATSU, Masaki IGARASHI, Atsushi SHIMADA, Hajime NAGAHARA, Rin-ichiro TANIGUCHI,
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Abstract(in English) In this paper, we propose a nonparametric background modeling for background subtraction using exponentially weighted histograms. Our background model is constructed by using exponentially increasing weights. We express our model by using recurrence formula. In our model, recently observed pixels have a bigger influence on the background model than older ones. The proposed model need not hold past pixel values in order to remove an old value from the model for updating. We confirmed that the proposed method is processed in real time experimentally and the accuracy of the background subtraction using our background model is comparable to that of conventional methods.
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Keyword(in English) Background subtraction / Background model / Kernel density estimation / Weighted histogram
Paper # CNR2013-50,PRMU2013-142
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Conference Information
Committee CNR
Conference Date 2014/2/6(1days)
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Registration To Cloud Network Robotics (CNR)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Background Modeling using Exponentially Weighted Histogram
Sub Title (in English)
Keyword(1) Background subtraction
Keyword(2) Background model
Keyword(3) Kernel density estimation
Keyword(4) Weighted histogram
1st Author's Name Tsubasa MINEMATSU
1st Author's Affiliation School of Engineering, Kyushu University()
2nd Author's Name Masaki IGARASHI
2nd Author's Affiliation Graduate Faculty of Information Science and Electrical Engineering, Kyushu University
3rd Author's Name Atsushi SHIMADA
3rd Author's Affiliation Faculty of Arts and Science, Kyushu University
4th Author's Name Hajime NAGAHARA
4th Author's Affiliation Graduate Faculty of Information Science and Electrical Engineering, Kyushu University
5th Author's Name Rin-ichiro TANIGUCHI
5th Author's Affiliation Graduate Faculty of Information Science and Electrical Engineering, Kyushu University
Date 2014/2/6
Paper # CNR2013-50,PRMU2013-142
Volume (vol) vol.113
Number (no) 432
Page pp.pp.-
#Pages 2
Date of Issue