Appearance-Based Motion Recognition of Human Actions

A new view-based approach to the representation and recognition of action is presented. The work is motivated by the observation that a human observer can easily and instantly recognize action in extremely low resolution imagery with no strong features or information about the three-dimensional structure of the scene. Our underlying representations for action are view-based descriptions of the coarse image motion. Using these descriptions, we propose an appearance-based recognition strategy embedded within a hypothesize-and-test paradigm. A binary motion region (BMR) image is initially computed to act as an index into the action library. The BMR grossly describes the spatial distribution of motion energy for a given view of a given action. Any stored BMRs that plausibly match the unknown input BMR are then tested for a coarse, categorical agreement with a known motion model of the action. We have developed two motion-based methods for the verification of the hypothesized actions. The f..