• DocumentCode
    2100631
  • Title

    Human motion segmentation and object recognition using fuzzy rules

  • Author

    Hunter, J.E.

  • Author_Institution
    Center for Intelligent Syst., Vanderbilt Univ., Nashville, TN, USA
  • fYear
    2005
  • fDate
    13-15 Aug. 2005
  • Firstpage
    210
  • Lastpage
    216
  • Abstract
    Our goal is to develop an object recognition and motion tracking system to assist in the analysis of data for a project in the psychology and human development department. Fuzzy membership rules provide a viable solution for creating this system. We describe our development of the feature vector, rule extraction, and image segmentation. The usefulness of the system is demonstrated via an analysis of videos of human action collected as part of an on-going collaboration with researchers in the Vanderbilt Psychology and Human Development department. Results are given to show the current progress, and future goals are presented.
  • Keywords
    image motion analysis; knowledge based systems; learning (artificial intelligence); object recognition; robot vision; social sciences computing; feature vector; fuzzy membership rules; fuzzy rules; human motion segmentation; image segmentation; motion tracking system; object recognition; rule extraction; Computer vision; Data analysis; Fuzzy systems; Humans; Image motion analysis; Motion analysis; Motion segmentation; Object recognition; Psychology; Tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robot and Human Interactive Communication, 2005. ROMAN 2005. IEEE International Workshop on
  • Print_ISBN
    0-7803-9274-4
  • Type

    conf

  • DOI
    10.1109/ROMAN.2005.1513781
  • Filename
    1513781