Attributed hypergraph representations for dynamic vision

Author

Rong, L. ; Wong, A.K.C.

Author_Institution

Pattern Analysis & Machine Intell. Group, Waterloo Univ., Ont., Canada

Volume

1

fYear

1996

Firstpage

498

Abstract

Investigates the use of an attributed hypergraph (AH) as a generic and hierarchical representation for dynamic vision, and examines its mathematical perspective in the framework of category theory. As shown in Kass et al. (1988), attributed hypergraph representation (AHR) is able to render a direct, general and flexible representation for describing objects/models with geometrical and physical features. With this representation, analysis and synthesis of structural/visual patterns can be carried out at different resolution levels. This paper presents the application of AHR in motion analysis and automatic morphing

Keywords

category theory; computer vision; graph theory; motion estimation; attributed hypergraph representations; automatic morphing; category theory; dynamic vision; flexible representation; geometrical features; hierarchical representation; motion analysis; physical features; structural/visual patterns; Animation; Automation; Deformable models; Machine intelligence; Machine vision; Motion analysis; Optimization methods; Pattern analysis; Psychology; Solid modeling;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1996., IEEE International Conference on

ISSN

1062-922X

Print_ISBN

0-7803-3280-6

Type

conf

DOI

10.1109/ICSMC.1996.569842

Filename

569842