About: Efficient Sampling of Disparity Space for Fast and Accurate Matching

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	A simple stereo matching algorithm is proposed that visits only a small fraction of disparity space in order to find a semi-dense disparity map. It works by growing from a small set of correspondence seeds. Unlike in known seedgrowing algorithms, it guarantees matching accuracy and correctness, even in the presence of repetitive patterns. This success is based on the fact it solves a global optimization task. The algorithm can recover from wrong initial seeds to the extent they can even be random. The quality of correspondence seeds influences computing time, not the quality of the final disparity map. We show that the proposed algorithm achieves similar results as an exhaustive disparity space search but it is two orders of magnitude faster. This is very unlike the existing growing algorithms which are fast but erroneous. A simple stereo matching algorithm is proposed that visits only a small fraction of disparity space in order to find a semi-dense disparity map. It works by growing from a small set of correspondence seeds. Unlike in known seedgrowing algorithms, it guarantees matching accuracy and correctness, even in the presence of repetitive patterns. This success is based on the fact it solves a global optimization task. The algorithm can recover from wrong initial seeds to the extent they can even be random. The quality of correspondence seeds influences computing time, not the quality of the final disparity map. We show that the proposed algorithm achieves similar results as an exhaustive disparity space search but it is two orders of magnitude faster. This is very unlike the existing growing algorithms which are fast but erroneous. (en) A simple stereo matching algorithm is proposed that visits only a small fraction of disparity space in order to find a semi-dense disparity map. It works by growing from a small set of correspondence seeds. Unlike in known seedgrowing algorithms, it guarantees matching accuracy and correctness, even in the presence of repetitive patterns. This success is based on the fact it solves a global optimization task. The algorithm can recover from wrong initial seeds to the extent they can even be random. The quality of correspondence seeds influences computing time, not the quality of the final disparity map. We show that the proposed algorithm achieves similar results as an exhaustive disparity space search but it is two orders of magnitude faster. This is very unlike the existing growing algorithms which are fast but erroneous. (cs)
Title	Efficient Sampling of Disparity Space for Fast and Accurate Matching Efficient Sampling of Disparity Space for Fast and Accurate Matching (en) Efficient Sampling of Disparity Space for Fast and Accurate Matching (cs)
skos:prefLabel	Efficient Sampling of Disparity Space for Fast and Accurate Matching Efficient Sampling of Disparity Space for Fast and Accurate Matching (en) Efficient Sampling of Disparity Space for Fast and Accurate Matching (cs)
skos:notation	RIV/68407700:21230/07:03135193!RIV09-MSM-21230___
http://linked.open...avai/riv/aktivita	P R
http://linked.open...avai/riv/aktivity	P(1ET101210406), R
http://linked.open...vai/riv/dodaniDat	2009
http://linked.open...aciTvurceVysledku	Šára, Radim Čech, Jan
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
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	419364
http://linked.open...ai/riv/idVysledku	RIV/68407700:21230/07:03135193
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	correspondence; growing; matching; pattern; random; repetitve; robust; seeds; stable; stereo (en)
http://linked.open.../riv/klicoveSlovo	correspondence growing robust matching pattern seeds random stereo repetitve stable
http://linked.open...ontrolniKodProRIV	[5EDDA51719B3]
http://linked.open...v/mistoKonaniAkce	Minneapolis
http://linked.open...i/riv/mistoVydani	Los Alamitos
http://linked.open...i/riv/nazevZdroje	CVPR 2007: Proceedings of the Computer Vision and Pattern Recognition conference
http://linked.open...in/vavai/riv/obor	JD
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	2 (xsd:int)
http://linked.open...vavai/riv/projekt	Automatic 3D Virtual Model Builder from Photographs
http://linked.open...UplatneniVysledku	2007
http://linked.open...iv/tvurceVysledku	Čech, Jan Šára, Radim
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2007-06-18 (xsd:date)
issn	1053-587X
number of pages	8 (xsd:int)
http://purl.org/ne...btex#hasPublisher	IEEE Computer Society
https://schema.org/isbn	1-4244-1180-7
http://localhost/t...ganizacniJednotka	21230

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