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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F07%3A03135193%21RIV09-MSM-21230___
rdf:type
skos:Concept n18:Vysledek
dcterms: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. 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.
dcterms:title
Efficient Sampling of Disparity Space for Fast and Accurate Matching Efficient Sampling of Disparity Space for Fast and Accurate Matching Efficient Sampling of Disparity Space for Fast and Accurate Matching
skos:prefLabel
Efficient Sampling of Disparity Space for Fast and Accurate Matching Efficient Sampling of Disparity Space for Fast and Accurate Matching Efficient Sampling of Disparity Space for Fast and Accurate Matching
skos:notation
RIV/68407700:21230/07:03135193!RIV09-MSM-21230___
n3:aktivita
n11:R n11:P
n3:aktivity
P(1ET101210406), R
n3:dodaniDat
n13:2009
n3:domaciTvurceVysledku
n7:9680411 n7:8930112
n3:druhVysledku
n15:D
n3:duvernostUdaju
n21:S
n3:entitaPredkladatele
n12:predkladatel
n3:idSjednocenehoVysledku
419364
n3:idVysledku
RIV/68407700:21230/07:03135193
n3:jazykVysledku
n14:eng
n3:klicovaSlova
correspondence; growing; matching; pattern; random; repetitve; robust; seeds; stable; stereo
n3:klicoveSlovo
n4:random n4:matching n4:growing n4:seeds n4:repetitve n4:correspondence n4:stable n4:pattern n4:stereo n4:robust
n3:kontrolniKodProRIV
[5EDDA51719B3]
n3:mistoKonaniAkce
Minneapolis
n3:mistoVydani
Los Alamitos
n3:nazevZdroje
CVPR 2007: Proceedings of the Computer Vision and Pattern Recognition conference
n3:obor
n8:JD
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n17:1ET101210406
n3:rokUplatneniVysledku
n13:2007
n3:tvurceVysledku
Čech, Jan Šára, Radim
n3:typAkce
n10:WRD
n3:zahajeniAkce
2007-06-18+02:00
s:issn
1053-587X
s:numberOfPages
8
n19:hasPublisher
IEEE Computer Society
n16:isbn
1-4244-1180-7
n20:organizacniJednotka
21230