RT Journal Article
T1 The non-parametric Parzen's window in stereo vision matching
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. From these attributes we compute a matching probability between pairs of features of the stereo images. A correspondence is said true when such a probability is maximum. We introduce a nonparametric strategy based on Parzen's window to estimate a probability density function (PDF) which is used to obtain the matching probability. This is the main finding of the paper. A comparative analysis of other recent matching methods is included to show that this finding can be justified theoretically. A generalization of the proposed method is made in order to give guidelines about its use with the similarity constraint and also in different environments where other features and attributes are more suitable.
PB Electronics Engineers Inc
SN 1083-4419
YR 2002
FD 2002-04
LK https://hdl.handle.net/20.500.14352/59128
UL https://hdl.handle.net/20.500.14352/59128
LA eng
NO © 2002 IEEE.The authors would like to thank the reviewers and Associate Editor for constructive recommendations.
DS Docta Complutense
RD 18 abr 2025