Modelling and recognising 3D-objects described by multiple views using function-described graphs

Author

Serratosa, Francesc ; Sanfeliu, Alberto ; Alquézar, René

Volume

2

fYear

2002

fDate

2002

Firstpage

140

Abstract

In this paper we study the application of Function-Described Graphs (FDGs) for 3D-object modeling and recognition. From a set of topologically different 2D-views taken of an object, FDGs are synthesized from the attributed adjacency graphs that are extracted for each view. It is shown that, by keeping in the object representation (an FDG) qualitative information of the second-order joint probabilities between vertices, the object recognition ratio increases while the run time of the classification process decreases.

Keywords

graph theory; image classification; image representation; object recognition; probability; 3D-object modeling; 3D-object recognition; antagonism relations; attributed adjacency graphs; classification process run time; existence relations; function-described graphs; multiple views; object recognition ratio; object representation; occurrence relations; second-order joint probabilities; topologically different 2D-views; Computational efficiency; Costs; Data mining; Data structures; Distributed computing; Object recognition; Probability distribution; Random variables;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 2002. Proceedings. 16th International Conference on

ISSN

1051-4651

Print_ISBN

0-7695-1695-X

Type

conf

DOI

10.1109/ICPR.2002.1048257

Filename

1048257