Hierarchical analysis of visual motion

Author

Meghabghab, G. ; Kandel, A.

Author_Institution

Dept. of Comput. Sci., Valdosta State Coll., GA, USA

Volume

22

Issue

4

fYear

1992

Firstpage

813

Lastpage

820

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;

fLanguage

English

Journal_Title

Systems, Man and Cybernetics, IEEE Transactions on

Publisher

ieee

ISSN

0018-9472

Type

jour

DOI

10.1109/21.156593

Filename

156593