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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F14%3A00218867%21RIV15-GA0-21230___
rdf:type
n12:Vysledek skos:Concept
rdfs:seeAlso
http://dx.doi.org/10.1007/978-3-319-04298-5_4
dcterms:description
We explore the performance of the recently proposed two-view image matchin g algorithms using affine view synthesis ASIFT (Morel and Yu, 2009) [14] and MODS (Mishkin, Perdoch and Matas, 2013) [10] on images of objects that do not have significant local texture and that are l ocally not well approximated by planes. Experiments show that view synthesis improves matching resul ts on images of such objects, but the number of useful synthetic views is lower than for planar objects matching. The best detector for matching images of 3D objects is the Hessian-Affine in the Sparse configuration. The iterative MODS matcher performs comparably confirming it is a robust, generic method for two view matching that performs well for different types of scenes and a wide range of viewing conditions. We explore the performance of the recently proposed two-view image matchin g algorithms using affine view synthesis ASIFT (Morel and Yu, 2009) [14] and MODS (Mishkin, Perdoch and Matas, 2013) [10] on images of objects that do not have significant local texture and that are l ocally not well approximated by planes. Experiments show that view synthesis improves matching resul ts on images of such objects, but the number of useful synthetic views is lower than for planar objects matching. The best detector for matching images of 3D objects is the Hessian-Affine in the Sparse configuration. The iterative MODS matcher performs comparably confirming it is a robust, generic method for two view matching that performs well for different types of scenes and a wide range of viewing conditions.
dcterms:title
Matching of Images of Non-planar Objects with View Synthesis Matching of Images of Non-planar Objects with View Synthesis
skos:prefLabel
Matching of Images of Non-planar Objects with View Synthesis Matching of Images of Non-planar Objects with View Synthesis
skos:notation
RIV/68407700:21230/14:00218867!RIV15-GA0-21230___
n3:aktivita
n23:P
n3:aktivity
P(GBP103/12/G084)
n3:dodaniDat
n15:2015
n3:domaciTvurceVysledku
Mishkin, Dmytro n18:1711326
n3:druhVysledku
n22:D
n3:duvernostUdaju
n9:S
n3:entitaPredkladatele
n21:predkladatel
n3:idSjednocenehoVysledku
27531
n3:idVysledku
RIV/68407700:21230/14:00218867
n3:jazykVysledku
n20:eng
n3:klicovaSlova
feature detectors; view synthesis; image matching
n3:klicoveSlovo
n13:feature%20detectors n13:image%20matching n13:view%20synthesis
n3:kontrolniKodProRIV
[7CAFE773B6AA]
n3:mistoKonaniAkce
High Tatras
n3:mistoVydani
Cham
n3:nazevZdroje
SOFSEM 2014: Theory and Practice of Computer Science
n3:obor
n10:JD
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n16:GBP103%2F12%2FG084
n3:rokUplatneniVysledku
n15:2014
n3:tvurceVysledku
Matas, Jiří Mishkin, Dmytro
n3:typAkce
n5:WRD
n3:wos
000342283300004
n3:zahajeniAkce
2014-01-26+01:00
s:issn
0302-9743
s:numberOfPages
10
n14:doi
10.1007/978-3-319-04298-5_4
n6:hasPublisher
Springer International Publishing AG
n19:isbn
978-3-319-04297-8
n17:organizacniJednotka
21230