Evaluation report of integrated background modeling based on spatio-temporal features

Yosuke Nonaka, Atsushi Shimada, Hajime Nagahara, Rin Ichiro Taniguchi

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

46 被引用数 (Scopus)

抄録

We report evaluation results of an integrated background modeling based on spatio-temporal features. The background modeling method consists of three complementary approaches: pixel-level background modeling, region-level one and frame-level one. The pixel-level background model uses the probability density function to approximate background model. The PDF is estimated non-parametrically by using Parzen density estimation. The region-level model is based on the evaluation of the local texture around each pixel while reducing the effects of variations in lighting. The frame-level model detects sudden, global changes of the the image brightness and estimates a present background image from input image referring to a background model image. Then, objects are extracted by background subtraction. Fusing these approaches realizes robust object detection under varying illumination.

本文言語英語
ホスト出版物のタイトル2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2012
ページ9-14
ページ数6
DOI
出版ステータス出版済み - 2012
イベント2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2012 - Providence, RI, 米国
継続期間: 6月 16 20126月 21 2012

出版物シリーズ

名前IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
ISSN(印刷版)2160-7508
ISSN(電子版)2160-7516

その他

その他2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2012
国/地域米国
CityProvidence, RI
Period6/16/126/21/12

!!!All Science Journal Classification (ASJC) codes

  • コンピュータ ビジョンおよびパターン認識
  • 電子工学および電気工学

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