移動方向変化に対応した立体高次自己局所相関特徴を用いた人物動作識別  [in Japanese] Human Behavior Detection Using Direction Change Invariant Features of Cubic Higher Order Local Auto Correlation  [in Japanese]

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Author(s)

Abstract

本論文では、立体高次自己相関特徴(CHLAC)を用いた人物動作判別において、人物の方向変化に頑健な特徴量処理の手法を提案する。CHLAC特徴量を用いた人物動作認識において、人物の移動方向のが変化が大きい動画像の場合、ベクトルの変化が大きくなるため、人物動作の判別が難しい場合がある。そのため移動方向変化に対応するため、移動方向変化を考慮したマスクパターン処理を提案する。コンピュータによる実験を行い、人物の大きさが変化する動画像において人物の異常動作が正しく特定できることを示す。

In this paper, we propose a new method of feature homogenization to prevent changes in the features according to human subtle direction change, in the detection of the human behavior of CHLAC. The conventional human behavior detection using CHLAC, it shows a high performance, but the situation that moving greatly changes the direction of the vector, abnormal operation and normal operation if it is difficult to determine the present. we propose a method in addition to improved handling and statistical processing mask pattern to suppress the change in the amount of features according to the direction of movement of the person. This provides a robust human motion specific person to change direction. Computer simulation using moving images of human is performed with the proposed scheme. The experimental results showed that the proposed scheme has a better than these conventional schemes in recognization of abnormal human behaviors.

Journal

  • IEICE technical report. Image engineering

    IEICE technical report. Image engineering 112(248), 1-6, 2012-10-11

    The Institute of Electronics, Information and Communication Engineers

References:  8

Codes

  • NII Article ID (NAID)
    110009636757
  • NII NACSIS-CAT ID (NCID)
    AN10013006
  • Text Lang
    JPN
  • Article Type
    ART
  • ISSN
    0913-5685
  • NDL Article ID
    024079628
  • NDL Call No.
    Z16-940
  • Data Source
    CJP  NDL  NII-ELS 
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