Efficient Sequential Correspondence Selection by Cosegmentation

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F10%3A00168986" target="_blank" >RIV/68407700:21230/10:00168986 - isvavai.cz</a>
Result on the web
<a href="http://doi.ieeecomputersociety.org/10.1109/TPAMI.2009.176" target="_blank" >http://doi.ieeecomputersociety.org/10.1109/TPAMI.2009.176</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TPAMI.2009.176" target="_blank" >10.1109/TPAMI.2009.176</a>

Result language
angličtina
Original language name
Efficient Sequential Correspondence Selection by Cosegmentation
Original language description
Object recognition and wide baseline stereo methods, correspondences of interest points (distinguished regions) are commonly established by matching compact descriptors such as SIFTs. We show that a subsequent cosegmentation process coupled with a quasi-optimal sequential decision process leads to a correspondence verification procedure that (i) has high precision (ii) has good recall and (iii) is fast. The sequential decision on the correctness of a correspondence is based on simple statistics of a modified dense stereo matching algorithm. The statistics are projected on a prominent discriminative direction by SVM. Wald's sequential probability ratio test is performed on the SVM projection computed on progressively larger cosegmented regions.We show experimentally that the proposed Sequential Correspondence Verification (SCV) algorithm significantly outperforms the correspondence selection method based on SIFT distance ratios.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical
IEEE Transactions on Pattern Analysis and Machine Intelligence
ISSN
0162-8828
e-ISSN
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Volume of the periodical
32
Issue of the periodical within the volume
9
Country of publishing house
US - UNITED STATES
Number of pages
14
Pages from-to
1568-1581
UT code for WoS article
000279969000003
EID of the result in the Scopus database
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