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Proceedings Paper

Recognition and location of real objects using eigenimages and a neural network classifier
Author(s): Maria Asuncion Vicente; Oscar Reinoso; Carlos Perez; Cesar Fernandez; Jose Maria Sabater
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Paper Abstract

A representation using eigenimages that achieves in two stages identify the object and locate its pose is addressed.In this paper we demonstrate how a mixture of two approaches based on eigenspaces with some little modifications resolve the problem of identification and the location of the object. In the first stage we recognize the object by means of PCA* (Principal Component Analysis) method combined with a neural network classifier, and in the second step, the object’s pose is obtained using a modification of typical PCA (we name as PCA2 method). We present the results obtained using a database made with 25 real objects.

Paper Details

Date Published: 23 June 2003
PDF: 8 pages
Proc. SPIE 5150, Visual Communications and Image Processing 2003, (23 June 2003); doi: 10.1117/12.502688
Show Author Affiliations
Maria Asuncion Vicente, Univ. Miguel Hernández de Elche (Spain)
Oscar Reinoso, Univ. Miguel Hernández de Elche (Spain)
Carlos Perez, Univ. Miguel Hernández de Elche (Spain)
Cesar Fernandez, Univ. Miguel Hernández de Elche (Spain)
Jose Maria Sabater, Univ. Miguel Hernández de Elche (Spain)


Published in SPIE Proceedings Vol. 5150:
Visual Communications and Image Processing 2003
Touradj Ebrahimi; Thomas Sikora, Editor(s)

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