Stereo matching based on the self-organizing feature-mapping algorithm

Pajares, Gonzalo, Cruz García, Jesús Manuel de la y Aranda Almansa, Joaquín . (1998) Stereo matching based on the self-organizing feature-mapping algorithm. Pattern Recognition Letters (19), p. 319–330


Título Stereo matching based on the self-organizing feature-mapping algorithm
Autor(es) Pajares, Gonzalo
Cruz García, Jesús Manuel de la
Aranda Almansa, Joaquín
Materia(s) Informática
Resumen This paper presents an approach to the local stereo matching problem using edge segments as features with several attributes. We have verified that the differences in attributes for the true matches cluster in a cloud around a center. The correspondence is established on the basis of the minimum squared Mahalanobis distance between the difference of the attributes for a current pair of features and the cluster center (similarity constraint). We introduce a learning strategy based on the Self-Organizing feature-mapping method to get the best cluster center. A comparative analysis among methods without learning is illustrated
Palabras clave Self-organizing feature-mapping
Local matching
Stereovision
Learning
Training
Editor(es) Elsevier
Fecha 1998-01-01
Formato application/pdf
Identificador PCA98
bibliuned:676
Publicado en la Revista Pattern Recognition Letters (19), p. 319–330
Idioma eng
Versión de la publicación publishedVersion
Tipo de recurso Article
Derechos de acceso y licencia http://creativecommons.org/licenses/by-nc-nd/4.0
info:eu-repo/semantics/openAccess
Tipo de acceso Acceso abierto

 
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Creado: Fri, 16 Nov 2007, 15:32:52 CET