Background light ray modeling for change detection

研究成果: ジャーナルへの寄稿学術誌査読

2 被引用数 (Scopus)


This paper is an extension of the work that was originally reported in Shimada et al. (2013). This paper proposes a change detection method based on spatio-temporal light ray consistency. The proposed method introduces light field sensing, which is used to generate an arbitrary in-focus plane. Change detection is performed in a surveillance scene, where the background region can be filtered out by an out-focusing process. This approach resolves a longstanding issue in background modeling-based object detection, which often suffers from false positives in the background regions. To realize this new change detection method, a new feature representation, called the local ray pattern (LRP), is introduced. The LRP evaluates the spatial consistency of the light rays, and this plays an important role in distinguishing whether the light rays come from the in-focus plane or elsewhere. A combination of the LRP and Gaussian mixture model (GMM)-based background modeling realizes change detection in the in-focus plane. Experimental results demonstrate the proposed method's effectiveness and its applicability to video surveillance.

ジャーナルJournal of Visual Communication and Image Representation
出版ステータス出版済み - 7月 1 2016

!!!All Science Journal Classification (ASJC) codes

  • 信号処理
  • メディア記述
  • 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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