Title :
Hierarchical analysis of visual motion
Author :
Meghabghab, G. ; Kandel, A.
Author_Institution :
Dept. of Comput. Sci., Valdosta State Coll., GA, USA
Abstract :
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
Keywords :
biology computing; correlation methods; data structures; physiological models; visual perception; binary images; biology computing; component directional selectivity; cortical level; hierarchical correlation; hierarchical data structure; pattern directional selectivity; physiological model; retinal level; visual motion; visual perception; Band pass filters; Brain modeling; Computer science; Filtering; Frequency; Image motion analysis; Motion analysis; Retina; Shape; Visual system;
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on
