Cognition helps vision: Recognizing biological motion using invariant dynamic cues

Abstract

This paper considers the problem of designing computational models of the primitives that are at the basis of the visual perception of motion in humans. The main contribution of this work is to establish a connection between cognitive science observations and empirical computational modeling. We take inspiration from the very first stage of the human development, and address the problem of understanding the presence of biological motion in the scene. To this end, we investigate the use of coarse motion descriptors composed by low-level features inspired by the Two-Thirds Power Law. In the experimental analysis, we first discuss the validity of the Two-Thirds Power Law in the context of video analysis, where, to the best of our knowledge, it has not found application so far. Second, we show a preliminary investigation on the use of a very simple motion model for characterizing biological motion with respect to non-biological dynamic events.