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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F09%3A00161364%21RIV10-AV0-21230___
rdf:type
skos:Concept n18:Vysledek
dcterms:description
We present a novel algorithm for image-based surface reconstruction from a set of calibrated images. The problem is formulated in Bayesian framework, where estimates of depth and visibility in a set of selected cameras are iteratively improved. The core of the algorithm is the minimisation of overall geometric L_2 error between measured 3D points and the depth estimates. In the visibility estimation task, the algorithm aims at outlier detection and noise suppression, as both types of errors are often present in the stereo output. The geometrical formulation allows for simultaneous refinement of the external camera parameters, which is an essential step for obtaining accurate results even when the calibration is not precisely known. We show that the results obtained with our method are comparable to other state-of-the-art techniques. We present a novel algorithm for image-based surface reconstruction from a set of calibrated images. The problem is formulated in Bayesian framework, where estimates of depth and visibility in a set of selected cameras are iteratively improved. The core of the algorithm is the minimisation of overall geometric L_2 error between measured 3D points and the depth estimates. In the visibility estimation task, the algorithm aims at outlier detection and noise suppression, as both types of errors are often present in the stereo output. The geometrical formulation allows for simultaneous refinement of the external camera parameters, which is an essential step for obtaining accurate results even when the calibration is not precisely known. We show that the results obtained with our method are comparable to other state-of-the-art techniques.
dcterms:title
Depth Map Fusion with Camera Position Refinement Depth Map Fusion with Camera Position Refinement
skos:prefLabel
Depth Map Fusion with Camera Position Refinement Depth Map Fusion with Camera Position Refinement
skos:notation
RIV/68407700:21230/09:00161364!RIV10-AV0-21230___
n3:aktivita
n6:P
n3:aktivity
P(1ET101210406)
n3:dodaniDat
n4:2010
n3:domaciTvurceVysledku
n10:7065388 n10:8930112
n3:druhVysledku
n21:D
n3:duvernostUdaju
n11:S
n3:entitaPredkladatele
n15:predkladatel
n3:idSjednocenehoVysledku
309525
n3:idVysledku
RIV/68407700:21230/09:00161364
n3:jazykVysledku
n17:eng
n3:klicovaSlova
computer vision; surface reconstruction
n3:klicoveSlovo
n7:surface%20reconstruction n7:computer%20vision
n3:kontrolniKodProRIV
[33621DAFE0C2]
n3:mistoKonaniAkce
Eibiswald
n3:mistoVydani
Wien
n3:nazevZdroje
CVWW 2009: Computer Vision Winter Workshop 2009
n3:obor
n8:JD
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n16:1ET101210406
n3:rokUplatneniVysledku
n4:2009
n3:tvurceVysledku
Šára, Radim Tyleček, Radim
n3:typAkce
n14:WRD
n3:zahajeniAkce
2009-02-04+01:00
s:numberOfPages
8
n19:hasPublisher
Pattern Recognition & Image Processing Group, Vienna University of Technology
n20:isbn
978-3-200-01390-2
n13:organizacniJednotka
21230