Hierarchical analysis of visual motion
George Meghabghab, Abraham Kandel · IEEE Transactions on Systems Man and Cybernetics · 1992
A hierarchical data structure for analyzing visual motion is presented. Although the literature on perception is abundant with studies on visual motion, none of the studies investigated the importance of a hierarchical model in the analysis of visual motion. The model was implemented on a supercomputer (Cyber 205). The algorithms of hierarchical correlation were performed on binary images. The results are compared with those obtained using similar serial algorithms. The impact of such a hierarchy on component directional selectivity and on pattern directional selectivity is studied.>