Approximate Models for Fast and Accurate Epipolar Geometry Estimation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F13%3A00212575" target="_blank" >RIV/68407700:21230/13:00212575 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/IVCNZ.2013.6727000" target="_blank" >http://dx.doi.org/10.1109/IVCNZ.2013.6727000</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/IVCNZ.2013.6727000" target="_blank" >10.1109/IVCNZ.2013.6727000</a>
Alternative languages
Result language
angličtina
Original language name
Approximate Models for Fast and Accurate Epipolar Geometry Estimation
Original language description
This paper investigates the plausibility of using approximate models for hypothesis generation in a RANSAC framework to accurately and reliably estimate the fundamental matrix. Two novel fundamental matrix estimators are introduced that sample two correspondences to generate affine-fundamental matrices for RANSAC hypotheses. A new RANSAC framework is presented that uses local optimization to estimate the fundamental matrix from the consensus correspondence sets of verified hy- potheses, which are approximate models. The proposed estimators are shown to perform better than other approximate models that have previously been used in the literature for fundamental matrix estimation in a rigorous evaluation. In addition the proposed estimators are over 30 times faster, in terms of models verified, than the 7-point method, and offer comparable accuracy and repeatability on a large subset of the test set.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2013 28th International Conference of Image and Vision Computing New Zealand (IVCNZ 2013)
ISBN
978-1-4799-0882-0
ISSN
2151-2191
e-ISSN
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Number of pages
6
Pages from-to
106-111
Publisher name
IEEE
Place of publication
Piscataway
Event location
Wellington
Event date
Nov 27, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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