About: Two-View Matching with View Synthesis Revisited

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	Wide-baseline matching, focussing on challenging problems e.g. with extreme viewpoint change,is considered. We introduce the use of view synthesis with affine-covariant detectors to solve such problems and show that matching with the Hessian-Affine or MSER detectors outperforms the state-of-the-art ASIFT. To minimise the loss of speed caused by view synthesis, we propose the Matching On Demand with view Synthesis algorithm (MODS) that uses progressively more synthesized images and more (time-consuming) detectors until reliable estimation of geometry is possible. We show experimentally that the MODS algorithm solves matching problems beyond the state-of-the-art and yet is comparable in speed to standard wide-baseline matchers on simpler problems. Minor contributions include an improved method for tentative correspondence selection, applicable both with and without view synthesis and a discovery of a view synthesis set up greatly improving MSER robustness to blur and scale change that increase its running time by 10% only. Wide-baseline matching, focussing on challenging problems e.g. with extreme viewpoint change,is considered. We introduce the use of view synthesis with affine-covariant detectors to solve such problems and show that matching with the Hessian-Affine or MSER detectors outperforms the state-of-the-art ASIFT. To minimise the loss of speed caused by view synthesis, we propose the Matching On Demand with view Synthesis algorithm (MODS) that uses progressively more synthesized images and more (time-consuming) detectors until reliable estimation of geometry is possible. We show experimentally that the MODS algorithm solves matching problems beyond the state-of-the-art and yet is comparable in speed to standard wide-baseline matchers on simpler problems. Minor contributions include an improved method for tentative correspondence selection, applicable both with and without view synthesis and a discovery of a view synthesis set up greatly improving MSER robustness to blur and scale change that increase its running time by 10% only. (en)
Title	Two-View Matching with View Synthesis Revisited Two-View Matching with View Synthesis Revisited (en)
skos:prefLabel	Two-View Matching with View Synthesis Revisited Two-View Matching with View Synthesis Revisited (en)
skos:notation	RIV/68407700:21230/13:00212526!RIV14-TA0-21230___
http://linked.open...avai/predkladatel	Fakulta elektrotechnická
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(GBP103/12/G084), P(TE01020415)
http://linked.open...vai/riv/dodaniDat	2014
http://linked.open...aciTvurceVysledku	Matas, Jiří Perďoch, Michal Mishkin, Dmytro
http://linked.open.../riv/druhVysledku	O - Ostatní výsledky nezařaditelné do žádného z výše uvedených druhů výsledku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	České vysoké učení technické v Praze / Fakulta elektrotechnická
http://linked.open...dnocenehoVysledku	112202
http://linked.open...ai/riv/idVysledku	RIV/68407700:21230/13:00212526
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	matching; wide baseline stereo; MSER; SIFT; extreme views (en)
http://linked.open.../riv/klicoveSlovo	matching SIFT MSER extreme views wide baseline stereo
http://linked.open...ontrolniKodProRIV	[50F32AFFD3F9]
http://linked.open...in/vavai/riv/obor	JD
http://linked.open...ichTvurcuVysledku	3 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	Center for Large Scale Multi-modal Data Interpretation V3C - Visual Computing Competence Center
http://linked.open...UplatneniVysledku	2013
http://linked.open...iv/tvurceVysledku	Matas, Jiří Perďoch, Michal Mishkin, Dmytro
http://localhost/t...ganizacniJednotka	21230

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