RT Journal Article
T1 Stereovision matching through support vector machines
A1 Pajares Martínsanz, Gonzalo
A1 Cruz García, Jesús Manuel de la
AB This paper presents an approach to the local stereovision matching problem using edge segments as features with four attributes. In this paper we design a Support Vector Machine classifier for solving the stereovision matching problem. We obtain a matching decision function to classify a pair of features as a true or false match. The use of such classifier makes up the main finding of the paper. A comparative analysis among other existing approaches is included to show that this finding can be justified theoretically. From these investigations, we conclude that the performance of the proposed method is appropriate for this task.
PB Elsevier Science BV
SN 0167-8655
YR 2003
FD 2003-11
LK https://hdl.handle.net/20.500.14352/51088
UL https://hdl.handle.net/20.500.14352/51088
LA eng
NO Part of the work has been performed underproject CICYT TAP94-0832-C02-01.
NO CICYT
DS Docta Complutense
RD 15 dic 2025