DocumentCode
1645346
Title
Geometric neurocomputing for visually pose recognition
Author
Bayro-Corrochano, Eduardo ; Vallejo, Refugio
Author_Institution
Dept. of Comput. Sci., Centro de Investigacion y de Estudios Avanzados, Guadalajara, Mexico
Volume
1
fYear
2002
fDate
6/24/1905 12:00:00 AM
Firstpage
251
Lastpage
256
Abstract
This paper presents a geometric neurocomputing approach for 3D pose recognition using the framework of the geometric Clifford algebras. The type of geometric problems like pose recognition can be very efficiently handled using geometric neural networks. Our experimental part shows the computing of 3D pose using 2D image data and the computing of 3D pose of rigid objects using visual information captured by a trinocular head
Keywords
computational geometry; computer vision; image recognition; neural nets; 2D image data; 3D pose recognition; geometric Clifford algebras; geometric neurocomputing; trinocular head; visual pose recognition; Algebra; Multidimensional systems; Neural networks; Neurons; Nonlinear equations; Solid modeling; Topology; Yttrium;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location
Honolulu, HI
ISSN
1098-7576
Print_ISBN
0-7803-7278-6
Type
conf
DOI
10.1109/IJCNN.2002.1005478
Filename
1005478
Link To Document