The Human Action Image
Recognizing a person's motion is intuitive for humans but represents a challenging problem in machine vision. In this paper, we present a multi-disciplinary framework for recognizing human actions. We develop a novel descriptor, the Human Action Image (HAI): a physically-significant, compact representation for the motion of a person, which we derive from first principles in physics using Hamilton's Action. We embed the HAI as the Motion Energy Pathway of the latest Neurobiological model of motion recognition. The Form Pathway is modelled using existing low-level feature descriptors based on shape and appearance. Experimental validation of the theory is provided on the well-known Weizmann and USF Gait datasets.