• DocumentCode
    2538240
  • Title

    Improved Shape Context algorithm for online fast recognition -an application in pedestrian detection from a moving vehicle

  • Author

    Wang, Min ; Wang, Jian-Qing ; Qiao, Hong ; Cao, Xian-Bin

  • Author_Institution
    Inst. of Autom., Chinese Acad. of Sci., Beijing, China
  • fYear
    2009
  • fDate
    3-5 June 2009
  • Firstpage
    1260
  • Lastpage
    1264
  • Abstract
    Shape context algorithm is a recently proposed good method for object recognition. It is robust under small geometrical distortions and occlusion, invariant under scaling, translation, and change of illumination. However, because of its computational complexity, this algorithm is not suitable for online recognition. In this paper, we proposed an improved shape context algorithm which introduces an optimal hierarchical structure and gives new reference points selection criteria. Compared with the original shape context algorithm, the improved algorithm keeps the recognition accuracy and reduces the computational cost greatly. The good experimental results reveal that, this new algorithm can be applied to the pedestrian detection system online, which is an important research topic in intelligent transportation.
  • Keywords
    automated highways; computational complexity; object detection; object recognition; computational complexity; geometrical distortion; intelligent transportation; object recognition; online fast recognition; pedestrian detection system online; shape context algorithm; Change detection algorithms; Computational complexity; Computational efficiency; Intelligent transportation systems; Lighting; Object recognition; Robustness; Shape; Vehicle detection; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles Symposium, 2009 IEEE
  • Conference_Location
    Xi´an
  • ISSN
    1931-0587
  • Print_ISBN
    978-1-4244-3503-6
  • Electronic_ISBN
    1931-0587
  • Type

    conf

  • DOI
    10.1109/IVS.2009.5164464
  • Filename
    5164464