title: Significant body point labeling and tracking.
abstract: In this paper, a method is presented to label and track anatomical landmarks (e.g., head, hand/arm, feet), which are referred to as significant body points (SBPs), using implicit body models. By considering the human body as an inverted pendulum model, ellipse fitting and contour moments are applied to classify it as being in Stand, Sit, or Lie posture. A convex hull of the silhouette contour is used to determine the locations of SBPs. The particle filter or a motion flow-based method is used to predict SBPs in occlusion. Stick figures of various activities are generated by connecting the SBPs. The qualitative and quantitative evaluation show that the proposed method robustly labels and tracks SBPs in various activities of two different (low and high) resolution data sets.
authors.forename: Faisal
authors.initials: F
authors.lastname: Azhar
authors.forename: Tardi
authors.initials: T
authors.lastname: Tjahjadi
mesh_terms: D000465:Algorithms; D000886:Anthropometry / Q000379:methods*; D018594:Human Body; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008954:Models, Biological; D011187:Posture; D014741:Video Recording