2026-06-27T22:45:17Zhttps://docta.ucm.es/rest/oai/requestoai:docta.ucm.es:20.500.14352/591282024-08-21T14:01:41Zcom_20.500.14352_14col_20.500.14352_15
Docta Complutense
author
Pajares Martínsanz, Gonzalo
author
Cruz García, Jesús Manuel de la
2023-06-20T19:01:38Z
2023-06-20T19:01:38Z
2002-04
1083-4419
10.1109/3477.990879
https://hdl.handle.net/20.500.14352/59128
http://dx.doi.org/10.1109/3477.990879
http://ieeexplore.ieee.org/
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.
eng
The non-parametric Parzen's window in stereo vision matching
journal article
URL
https://docta.ucm.es/bitstreams/c003d29c-ae66-4299-859d-4a43157c7950/download
File
MD5
f7f2ac201edd0681a0b173ec97b1b42c
277144
application/pdf
cruagarcia50.pdf