Robust Background Subtraction by Statistical Reach Feature on Random Reference Points

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2013/01/01

タイトル(英語): Robust Background Subtraction by Statistical Reach Feature on Random Reference Points

著者名: Kenji Iwata (National Institute of Advanced Industrial Science and Technology (AIST)), Yutaka Satoh (National Institute of Advanced Industrial Science and Technology (AIST)/Graduate School of Systems and Information Engineering, University of Tsukuba), Ry

著者名(英語): Kenji Iwata (National Institute of Advanced Industrial Science and Technology (AIST)), Yutaka Satoh (National Institute of Advanced Industrial Science and Technology (AIST)/Graduate School of Systems and Information Engineering, University of Tsukuba), Ryushi Ozaki (Graduate School of Systems and Information Engineering, University of Tsukuba), Katsuhiko Sakaue (National Institute of Advanced Industrial Science and Technology (AIST)/Graduate School of Systems and Information Engineering, University of Tsukuba)

キーワード: Background Subtraction，Statistical Reach Feature，Incremental Sign，Background model

要約(英語): Extracting a robust feature set in a given image sequence is an important fundamental technique that influences the performance of various computer vision systems. A statistic reach feature (SRF) is a stable feature for robust background subtraction. The SRF is defined as two arbitrary points that maintain the sign of the increase and decrease of the brightness in the image sequence. This paper describes the process of accelerating the construction of a background model using some point pairs chosen at random.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.133 No.1 （2013） 特集：2012 Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV2012)

本誌掲載ページ: 128-133 p

原稿種別: 論文／英語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/133/1/133_128/_article/-char/ja/