Efficient sequential correspondence selection by cosegmentation

In many retrieval, 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 decisio...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence. - 1979. - 32(2010), 9 vom: 15. Sept., Seite 1568-81
1. Verfasser: Cech, Jan (VerfasserIn)
Weitere Verfasser: Matas, Jirí, Perdoch, Michal
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2010
Zugriff auf das übergeordnete Werk:IEEE transactions on pattern analysis and machine intelligence
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
LEADER 01000naa a22002652 4500
001 NLM199615950
003 DE-627
005 20231223215010.0
007 cr uuu---uuuuu
008 231223s2010 xx |||||o 00| ||eng c
024 7 |a 10.1109/TPAMI.2009.176  |2 doi 
028 5 2 |a pubmed24n0665.xml 
035 |a (DE-627)NLM199615950 
035 |a (NLM)20634553 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Cech, Jan  |e verfasserin  |4 aut 
245 1 0 |a Efficient sequential correspondence selection by cosegmentation 
264 1 |c 2010 
336 |a Text  |b txt  |2 rdacontent 
337 |a ƒaComputermedien  |b c  |2 rdamedia 
338 |a ƒa Online-Ressource  |b cr  |2 rdacarrier 
500 |a Date Completed 27.12.2010 
500 |a Date Revised 16.07.2010 
500 |a published: Print 
500 |a Citation Status MEDLINE 
520 |a In many retrieval, 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 1) has high precision (is highly discriminative), 2) has good recall, and 3) 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 standard correspondence selection method based on SIFT distance ratios on challenging matching problems 
650 4 |a Journal Article 
650 4 |a Research Support, Non-U.S. Gov't 
700 1 |a Matas, Jirí  |e verfasserin  |4 aut 
700 1 |a Perdoch, Michal  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t IEEE transactions on pattern analysis and machine intelligence  |d 1979  |g 32(2010), 9 vom: 15. Sept., Seite 1568-81  |w (DE-627)NLM098212257  |x 1939-3539  |7 nnns 
773 1 8 |g volume:32  |g year:2010  |g number:9  |g day:15  |g month:09  |g pages:1568-81 
856 4 0 |u http://dx.doi.org/10.1109/TPAMI.2009.176  |3 Volltext 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_NLM 
912 |a GBV_ILN_350 
951 |a AR 
952 |d 32  |j 2010  |e 9  |b 15  |c 09  |h 1568-81