Image retrieval with relevance feedback based on graph-theoretic region correspondence estimation
This paper presents a graph-theoretic approach for region-based image retrieval. When dealing with image matching problem, we propose converting the region correspondence estimation into an attributed graph matching problem and measuring the image similarity in terms of both the region correspondenc...
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creator | Chuech-Yu Li Ming-Chou Shih Chiou-Ting Hsu |
description | This paper presents a graph-theoretic approach for region-based image retrieval. When dealing with image matching problem, we propose converting the region correspondence estimation into an attributed graph matching problem and measuring the image similarity in terms of both the region correspondence and the low-level features. In addition, during the relevance feedback, we propose using a maximum likelihood method to re-estimate region features and region importance while retaining its inherent spatial organization. Experimental results show that the proposed graph-theoretic matching criterion outperforms other existing methods which include no spatial information in the matching criterion. The experiments also show that the performance can be further improved with our proposed relevance feedback scheme. |
doi_str_mv | 10.1109/ICPR.2004.1334659 |
format | Conference Proceeding |
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When dealing with image matching problem, we propose converting the region correspondence estimation into an attributed graph matching problem and measuring the image similarity in terms of both the region correspondence and the low-level features. In addition, during the relevance feedback, we propose using a maximum likelihood method to re-estimate region features and region importance while retaining its inherent spatial organization. Experimental results show that the proposed graph-theoretic matching criterion outperforms other existing methods which include no spatial information in the matching criterion. The experiments also show that the performance can be further improved with our proposed relevance feedback scheme.</description><identifier>ISSN: 1051-4651</identifier><identifier>ISBN: 0769521282</identifier><identifier>ISBN: 9780769521282</identifier><identifier>EISSN: 2831-7475</identifier><identifier>DOI: 10.1109/ICPR.2004.1334659</identifier><language>eng</language><publisher>IEEE</publisher><subject>Computer science ; Content based retrieval ; Feedback ; Image converters ; Image databases ; Image matching ; Image representation ; Image retrieval ; Information retrieval ; Maximum likelihood estimation</subject><ispartof>Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004, 2004, Vol.3, p.842-845 Vol.3</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1334659$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,4050,4051,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1334659$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Chuech-Yu Li</creatorcontrib><creatorcontrib>Ming-Chou Shih</creatorcontrib><creatorcontrib>Chiou-Ting Hsu</creatorcontrib><title>Image retrieval with relevance feedback based on graph-theoretic region correspondence estimation</title><title>Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004</title><addtitle>ICPR</addtitle><description>This paper presents a graph-theoretic approach for region-based image retrieval. When dealing with image matching problem, we propose converting the region correspondence estimation into an attributed graph matching problem and measuring the image similarity in terms of both the region correspondence and the low-level features. In addition, during the relevance feedback, we propose using a maximum likelihood method to re-estimate region features and region importance while retaining its inherent spatial organization. Experimental results show that the proposed graph-theoretic matching criterion outperforms other existing methods which include no spatial information in the matching criterion. The experiments also show that the performance can be further improved with our proposed relevance feedback scheme.</description><subject>Computer science</subject><subject>Content based retrieval</subject><subject>Feedback</subject><subject>Image converters</subject><subject>Image databases</subject><subject>Image matching</subject><subject>Image representation</subject><subject>Image retrieval</subject><subject>Information retrieval</subject><subject>Maximum likelihood estimation</subject><issn>1051-4651</issn><issn>2831-7475</issn><isbn>0769521282</isbn><isbn>9780769521282</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2004</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotkNtKxDAQhoMHsLv6AOJNXqA1k0ObXsriobCgiF4vOUza6O52SYvi2xtxr4Zv5j_AEHINrAJg7W23enmtOGOyAiFkrdoTUnAtoGxko07JgjV1qzhwzc9IAUxBmUVwQRbT9MEYZ0LpgphuZ3qkCecU8cts6Xech4zbDHuHNCB6a9wntWZCT8c97ZM5DOU84JhN0WVtH_PajSnhdBj3Hv98OM1xZ-Z8uSTnwWwnvDrOJXl_uH9bPZXr58dudbcuIzRqLjWvbWCWo6uZNiCDbA1zwYLXXqHnWqHlsmmdEs62HlB61MFKn1lgkGJJbv5zIyJuDinXp5_N8TXiFyNVWOs</recordid><startdate>2004</startdate><enddate>2004</enddate><creator>Chuech-Yu Li</creator><creator>Ming-Chou Shih</creator><creator>Chiou-Ting Hsu</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2004</creationdate><title>Image retrieval with relevance feedback based on graph-theoretic region correspondence estimation</title><author>Chuech-Yu Li ; Ming-Chou Shih ; Chiou-Ting Hsu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-826bf0b2ec608a14f49a0cfb1d8d5ed285eb2479c53cb9d1e4de8fb4d53c3ef43</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Computer science</topic><topic>Content based retrieval</topic><topic>Feedback</topic><topic>Image converters</topic><topic>Image databases</topic><topic>Image matching</topic><topic>Image representation</topic><topic>Image retrieval</topic><topic>Information retrieval</topic><topic>Maximum likelihood estimation</topic><toplevel>online_resources</toplevel><creatorcontrib>Chuech-Yu Li</creatorcontrib><creatorcontrib>Ming-Chou Shih</creatorcontrib><creatorcontrib>Chiou-Ting Hsu</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Chuech-Yu Li</au><au>Ming-Chou Shih</au><au>Chiou-Ting Hsu</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Image retrieval with relevance feedback based on graph-theoretic region correspondence estimation</atitle><btitle>Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004</btitle><stitle>ICPR</stitle><date>2004</date><risdate>2004</risdate><volume>3</volume><spage>842</spage><epage>845 Vol.3</epage><pages>842-845 Vol.3</pages><issn>1051-4651</issn><eissn>2831-7475</eissn><isbn>0769521282</isbn><isbn>9780769521282</isbn><abstract>This paper presents a graph-theoretic approach for region-based image retrieval. When dealing with image matching problem, we propose converting the region correspondence estimation into an attributed graph matching problem and measuring the image similarity in terms of both the region correspondence and the low-level features. In addition, during the relevance feedback, we propose using a maximum likelihood method to re-estimate region features and region importance while retaining its inherent spatial organization. Experimental results show that the proposed graph-theoretic matching criterion outperforms other existing methods which include no spatial information in the matching criterion. The experiments also show that the performance can be further improved with our proposed relevance feedback scheme.</abstract><pub>IEEE</pub><doi>10.1109/ICPR.2004.1334659</doi></addata></record> |
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subjects | Computer science Content based retrieval Feedback Image converters Image databases Image matching Image representation Image retrieval Information retrieval Maximum likelihood estimation |
title | Image retrieval with relevance feedback based on graph-theoretic region correspondence estimation |
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