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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F05%3A03109907%21RIV06-AV0-21230___
rdf:type
skos:Concept n18:Vysledek
dcterms:description
Není k dispozici Automatic range image registration without any knowledge of the viewpoint requires identification of common regions across different range images and then establishing point correspondences in these regions. We formulate this as a graph-based optimization problem. More specifically, we define a graph in which each vertex represents a putative match of two points, each edge represents binary consistency decision between two matches, and each edge orientation represents match quality from worse to better putative match. Then strict sub-kernel defined in the graph is maximized. The maximum strict sub-kernel algorithm enables us to uniquely determine the largest consistent matching of points. To evaluate the quality of a single match, we employ the histogram of triple products that are generated by all surface normals in a point neighborhood. Our experimental results show the effectiveness of our method for coarse range image registration. Automatic range image registration without any knowledge of the viewpoint requires identification of common regions across different range images and then establishing point correspondences in these regions. We formulate this as a graph-based optimization problem. More specifically, we define a graph in which each vertex represents a putative match of two points, each edge represents binary consistency decision between two matches, and each edge orientation represents match quality from worse to better putative match. Then strict sub-kernel defined in the graph is maximized. The maximum strict sub-kernel algorithm enables us to uniquely determine the largest consistent matching of points. To evaluate the quality of a single match, we employ the histogram of triple products that are generated by all surface normals in a point neighborhood. Our experimental results show the effectiveness of our method for coarse range image registration.
dcterms:title
Globally Convergent Range Image Registration by Graph Kernel Algorithm Není k dispozici Globally Convergent Range Image Registration by Graph Kernel Algorithm
skos:prefLabel
Není k dispozici Globally Convergent Range Image Registration by Graph Kernel Algorithm Globally Convergent Range Image Registration by Graph Kernel Algorithm
skos:notation
RIV/68407700:21230/05:03109907!RIV06-AV0-21230___
n5:strany
377 ; 384
n5:aktivita
n12:P
n5:aktivity
P(1ET101210406), P(ME 678)
n5:dodaniDat
n6:2006
n5:domaciTvurceVysledku
n9:8930112
n5:druhVysledku
n17:D
n5:duvernostUdaju
n7:S
n5:entitaPredkladatele
n15:predkladatel
n5:idSjednocenehoVysledku
522804
n5:idVysledku
RIV/68407700:21230/05:03109907
n5:jazykVysledku
n16:eng
n5:klicovaSlova
computer graphics; computer vision; range image; registration
n5:klicoveSlovo
n13:range%20image n13:registration n13:computer%20graphics n13:computer%20vision
n5:kontrolniKodProRIV
[585BC2D201AA]
n5:mistoKonaniAkce
Ottawa
n5:mistoVydani
Los Alamitos
n5:nazevZdroje
3DIM 2005: Proceedings of 5th International Conference on 3-D Digital Imaging and Modeling
n5:obor
n19:JD
n5:pocetDomacichTvurcuVysledku
1
n5:pocetTvurcuVysledku
3
n5:projekt
n20:ME%20678 n20:1ET101210406
n5:rokUplatneniVysledku
n6:2005
n5:tvurceVysledku
Okatani, I. Šára, Radim Sugimoto, A.
n5:typAkce
n8:WRD
n5:zahajeniAkce
2005-06-13+02:00
s:numberOfPages
8
n3:hasPublisher
IEEE Computer Society Press
n11:isbn
0-7695-2327-7
n14:organizacniJednotka
21230