• DocumentCode
    3309555
  • Title

    Extended Histogram of Gradients feature for human detection

  • Author

    Satpathy, Amit ; Jiang, Xudong ; Eng, How-Lung

  • Author_Institution
    Sch. of EEE, Nanyang Technol. Univ., Singapore, Singapore
  • fYear
    2010
  • fDate
    26-29 Sept. 2010
  • Firstpage
    3473
  • Lastpage
    3476
  • Abstract
    Unsigned Histogram of Gradients (UHoG) is a popular feature used for human detection. Despite its superior performance as reported in recent literature, an inherent limitation of UHoG is that gradients of opposite directions in a cell are mapped into the same histogram bin. This is undesirable as it will produce the same UHoG feature for two different patterns. To address this problem, we propose a new feature named the Extended Histogram of Gradients (ExHoG) in this paper. It comprises two components: UHoG and a histogram of absolute bin value differences of opposite gradient directions computed from Histogram of Gradients (HoG). Our experimental results show that the proposed ExHoG consistently outperforms the standard HoG and UHoG for human detection.
  • Keywords
    feature extraction; image recognition; extended gradient histogram; histogram bin; human detection; unsigned histogram; Feature extraction; Histograms; Humans; Image edge detection; Pixel; Support vector machines; Training; Feature Extraction; Histogram of Gradients; HoG; Human Detection; Recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2010 17th IEEE International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4244-7992-4
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2010.5650070
  • Filename
    5650070