The authors present the theory of probabilistic relaxation for matching
symbolic structures, derive as limiting cases the various heuristic
formulas used by researchers in matching problems, and state the
conditions under which they apply. They successfully apply the theory
to the problem of matching and recognizing aerial road network images
based on road network models and to the problem of edge matching
in a stereo pair. For this purpose, each line network is represented
by an attributed relational graph where each node is a straight line
segment characterized by certain attributes and related with every
other node via a set of binary relations
%0 Journal Article
%1 Kittler1993
%A Kittler, J.
%A Christmas, W.J.
%A Petrou, M.
%D 1993
%J Computer Vision, 1993. Proceedings., Fourth International Conference
on
%K attributed attributes, binary computer edge formulas, graph, heuristic image images, line matching matching, models, network network, pair, probabilistic problems, processingaerial relational relations, relaxation, road segment, stereo straight structures symbolic vision,
%P 666-673
%R 10.1109/ICCV.1993.378148
%T Probabilistic relaxation for matching problems in computer vision
%X The authors present the theory of probabilistic relaxation for matching
symbolic structures, derive as limiting cases the various heuristic
formulas used by researchers in matching problems, and state the
conditions under which they apply. They successfully apply the theory
to the problem of matching and recognizing aerial road network images
based on road network models and to the problem of edge matching
in a stereo pair. For this purpose, each line network is represented
by an attributed relational graph where each node is a straight line
segment characterized by certain attributes and related with every
other node via a set of binary relations
@article{Kittler1993,
abstract = {The authors present the theory of probabilistic relaxation for matching
symbolic structures, derive as limiting cases the various heuristic
formulas used by researchers in matching problems, and state the
conditions under which they apply. They successfully apply the theory
to the problem of matching and recognizing aerial road network images
based on road network models and to the problem of edge matching
in a stereo pair. For this purpose, each line network is represented
by an attributed relational graph where each node is a straight line
segment characterized by certain attributes and related with every
other node via a set of binary relations},
added-at = {2009-09-12T19:19:34.000+0200},
author = {Kittler, J. and Christmas, W.J. and Petrou, M.},
biburl = {https://www.bibsonomy.org/bibtex/25c7b6be05c97fcc2acfb940c14270a4c/mozaher},
doi = {10.1109/ICCV.1993.378148},
file = {:Kittler1993.pdf:PDF},
interhash = {ceaa537d0b14ccae104ad33745e5fb32},
intrahash = {5c7b6be05c97fcc2acfb940c14270a4c},
journal = {Computer Vision, 1993. Proceedings., Fourth International Conference
on},
keywords = {attributed attributes, binary computer edge formulas, graph, heuristic image images, line matching matching, models, network network, pair, probabilistic problems, processingaerial relational relations, relaxation, road segment, stereo straight structures symbolic vision,},
month = May,
owner = {Mozaher},
pages = {666-673},
timestamp = {2009-09-12T19:19:40.000+0200},
title = {Probabilistic relaxation for matching problems in computer vision
},
year = 1993
}