Rectification, and Segmentation of Coplanar Repeated Patterns

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F14%3A00225691" target="_blank" >RIV/68407700:21230/14:00225691 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/CVPR.2014.380" target="_blank" >http://dx.doi.org/10.1109/CVPR.2014.380</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CVPR.2014.380" target="_blank" >10.1109/CVPR.2014.380</a>

Result language
angličtina
Original language name
Rectification, and Segmentation of Coplanar Repeated Patterns
Original language description
This paper presents a novel and general method for the detection, rectification and segmentation of imaged coplanar repeated patterns. The only assumption made of the scene geometry is that repeated scene elements are mapped to each other by planar Euclidean transformations. The class of patterns covered is broad and includes nearly all commonly seen, planar, man-made repeated patterns. In addition, novel linear constraints are used to reduce geometric ambiguity between the rectified imaged pattern andthe scene pattern. Rectification to within a similarity of the scene plane is achieved from one rotated repeat, or to within a similarity with a scale ambiguity along the axis of symmetry from one reflected repeat. A stratum of constraints is derived that gives the necessary configuration of repeats for each successive level of rectification. A generative model for the imaged pattern is inferred and used to segment the pattern with pixel accuracy. Qualitative results are shown on a broad
Czech name
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Czech description
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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)

Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
ISBN
978-1-4799-5117-8
ISSN
1063-6919
e-ISSN
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Number of pages
8
Pages from-to
2973-2980
Publisher name
IEEE Computer Society Press
Place of publication
Los Alamitos
Event location
Columbus, Ohio
Event date
Jun 23, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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