Could early visual processes be sufficient to label motions?

Biological motion recognition refers to our ability to recognize a scene (motion or movement) based on the evolution of a limited number of points acquired for instance with a motion capture tool. Much work has been done in this direction showing how it is possible to recognize actions based on these points. Following the reference work of Giese and Poggio (2003), we propose an alternative approach to extract such points from a video based on spiking neural networks with rank order coding. We use some recent results of Thorpe et al. (2001), who claim that the neural information is coded by the relative order in which these neurons fire. This allows selecting a limited set of relevant points to be used in the motion classification. Several experiments and comparisons with previous work are proposed. The result of these simulations is that information from early visual processes appears to be sufficient to classify biological motion.