• DocumentCode
    2298679
  • Title

    Human Motion Analysis

  • Author

    Tsai, Joseph C. ; Wong, Tzu-Lin ; Zhong, Hsing-Ying ; Chang, Shih-Ming ; Shih, Timothy K.

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Tamkang Univ., Tamsui, Taiwan
  • fYear
    2009
  • fDate
    7-9 July 2009
  • Firstpage
    373
  • Lastpage
    376
  • Abstract
    We propose a novel motion analysis algorithm by using the mean-shift segmentation and motion estimation technique. Mean shift algorithm is frequently used to extract objects from video according to its efficiency and robustness of non-rigid object tracking. For diminishing the computational complexity in searching process, an efficient block matching algorithm: cross-diamond-hexagonal search algorithm was used. In the motion analysis procedure, the stick figure of object obtained by thinning process is treated as guidance to gather the statistics of motion information. The experimental results show that the proposed method provides precise description of the behavior of object in several video sequences.
  • Keywords
    computational complexity; image matching; image segmentation; image sequences; motion estimation; video signal processing; block matching algorithm; computational complexity; cross-diamond-hexagonal search algorithm; human motion analysis; mean-shift segmentation; motion estimation technique; nonrigid object tracking; video object extraction; video sequences; Clustering algorithms; Computer science education; Filtering; Humans; Motion analysis; Motion estimation; Pervasive computing; Physics computing; Robustness; Tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Ubiquitous, Autonomic and Trusted Computing, 2009. UIC-ATC '09. Symposia and Workshops on
  • Conference_Location
    Brisbane, QLD
  • Print_ISBN
    978-1-4244-4902-6
  • Electronic_ISBN
    978-0-7695-3737-5
  • Type

    conf

  • DOI
    10.1109/UIC-ATC.2009.107
  • Filename
    5319210