Coplanar Repeats by Energy Minimization
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F16%3A00303936" target="_blank" >RIV/68407700:21230/16:00303936 - isvavai.cz</a>
Result on the web
<a href="http://ptak.felk.cvut.cz/personal/prittjam/bmvc16/index.html" target="_blank" >http://ptak.felk.cvut.cz/personal/prittjam/bmvc16/index.html</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Coplanar Repeats by Energy Minimization
Original language description
This paper proposes an automated method to detect, group and rectify arbitrarily arranged coplanar repeated elements via energy minimization. The proposed energy functional combines several features that model how planes with coplanar repeats are projected into images and captures global interactions between different coplanar repeat groups and scene planes. An inference framework based on a recent variant of α-expansion is described and fast convergence is demonstrated. We compare the proposed method to two widely-used geometric multi-model fitting methods using a new dataset of annotated images containing multiple scene planes with coplanar repeats in varied arrangements. The evaluation shows a significant improvement in the accuracy of rectifications computed from coplanar repeats detected with the proposed method versus those detected with the baseline methods.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/LL1303" target="_blank" >LL1303: Large Scale Category Retrieval</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the British Machine Vision Conference (BMVC) 2016
ISBN
1-901725-53-7
ISSN
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e-ISSN
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Number of pages
11
Pages from-to
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Publisher name
British Machine Vision Association
Place of publication
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Event location
York
Event date
Sep 19, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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