Accurate human detection by appearance and motion

Shaopeng Tang*, Satoshi Goto

*この研究の対応する著者

研究成果: Article査読

1 被引用数 (Scopus)

抄録

In this paper, a human detection method is developed. An appearance based detector and a motion based detector are proposed respectively. A multi scale block histogram of template feature (MB-HOT) is used to detect human by the appearance. It integrates the gray value information and the gradient value information, and represents the relationship of three blocks. Experiment on INRIA dataset shows that this feature is more discriminative than other features, such as histogram of orientation gradient (HOG). A motion based feature is also proposed to capture the relative motion of human body. This feature is calculated in optical flow domain and experimental result in our dataset shows that this feature outperforms other motion based features. The detection responses obtained by two features are combined to reduce the false detection. Graphic process unit (GPU) based implementation is proposed to accelerate the calculation of two features, and make it suitable for real time applications.

本文言語English
ページ(範囲)2728-2736
ページ数9
ジャーナルIEICE Transactions on Information and Systems
E93-D
10
DOI
出版ステータスPublished - 2010 10

ASJC Scopus subject areas

  • 電子工学および電気工学
  • ソフトウェア
  • 人工知能
  • ハードウェアとアーキテクチャ
  • コンピュータ ビジョンおよびパターン認識

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