• DocumentCode
    3468939
  • Title

    Human Body-Parts Tracking for Fine-Grained Behavior Classification

  • Author

    Ukita, Norimichi ; Nakazawa, Atsushi

  • fYear
    2013
  • fDate
    2-8 Dec. 2013
  • Firstpage
    777
  • Lastpage
    778
  • Abstract
    This paper discusses the usefulness of human body-parts tracking for acquiring subtle cues in social interactions. While many kinds of body-parts tracking algorithms have been proposed, we focus on particle filtering-based tracking using prior models, which have several advantages for researches on social interactions. As a first step for extracting subtle cues from videos of social interaction behaviors, the advantages, disadvantages, and prospective properties of the body-parts tracking using prior models are summarized with actual results.
  • Keywords
    behavioural sciences computing; feature extraction; image classification; object tracking; particle filtering (numerical methods); video signal processing; fine-grained behavior classification; human body-part tracking; particle filtering-based tracking; prior models; prospective properties; social interaction behavior videos; social interactions; subtle cues; Autism; Biological system modeling; Probabilistic logic; Robustness; Tracking; Trajectory; Videos; body-parts tracking; social interactions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision Workshops (ICCVW), 2013 IEEE International Conference on
  • Conference_Location
    Sydney, NSW
  • Type

    conf

  • DOI
    10.1109/ICCVW.2013.106
  • Filename
    6755975