• DocumentCode
    1687178
  • Title

    Detecting a human body direction using a feature selection method

  • Author

    Nakashima, Yuuki ; Tan, Joo Kooi ; Ishikawa, Seiji ; Morie, Takashi

  • Author_Institution
    Dept. of Mech. & Control Eng., Kyushu Inst. of Technol., Kitakyushu, Japan
  • fYear
    2010
  • Firstpage
    1424
  • Lastpage
    1427
  • Abstract
    This paper describes a novel technique for detecting a human body direction using SVM constructed by HOG feature selected by AdaBoost. HOG feature is well-known feature for the robust judgment of a human. We employ the feature for detecting a human body direction. We compared some feature selecting methods with the previous one. Experimental results show effectiveness of the proposed method.
  • Keywords
    feature extraction; learning (artificial intelligence); object detection; support vector machines; AdaBoost; HOG feature; SVM; feature detection; feature selection method; human body direction detection; Classification algorithms; Detectors; Feature extraction; Histograms; Humans; Support vector machines; Training; AdaBoost; HOG; Human body direction recognition; SVM; variance between classes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Automation and Systems (ICCAS), 2010 International Conference on
  • Conference_Location
    Gyeonggi-do
  • Print_ISBN
    978-1-4244-7453-0
  • Electronic_ISBN
    978-89-93215-02-1
  • Type

    conf

  • Filename
    5670329