A geometric radial basis function network for tracking variant 3D transformations

Author

Bayro-Corrochano, Eduardo ; Vazquez-Santacruz, Eduardo

Author_Institution

Dept. of Electr. Eng. & Comput. Sci., CINVESTAV Guadalajara, Jalisco, Mexico

fYear

2010

fDate

18-23 July 2010

Firstpage

1

Lastpage

6

Abstract

This paper presents a new hypercomplex valued Radial Basis Network. This network constitutes a generalization of the standard real valued RBF. This geometric RBF can be used in real time to estimate changes in linear transformations in 3D space between sets of geometric entities. Experiments using stereo image sequences validate this proposal. We show the tracking of changes in the orientation between sets of lines and planes. This is a promising approach for neural computing applications in visual guided robotics.

Keywords

image sequences; radial basis function networks; stereo image processing; geometric radial basis function network; geometric transformations; hypercomplex valued radial basis network; linear transformations; neural computing applications; stereo image sequences; variant 3D transformations; visual guided robotics; Algebra; Artificial neural networks; Blades; Radial basis function networks; Robots; Rotors; Training;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks (IJCNN), The 2010 International Joint Conference on

Conference_Location

Barcelona

ISSN

1098-7576

Print_ISBN

978-1-4244-6916-1

Type

conf

DOI

10.1109/IJCNN.2010.5596570

Filename

5596570