{"id":"https://openalex.org/W2118802082","doi":"https://doi.org/10.1109/iccv.2009.5459261","title":"An efficient algorithm for Co-segmentation","display_name":"An efficient algorithm for Co-segmentation","publication_year":2009,"publication_date":"2009-09-01","ids":{"openalex":"https://openalex.org/W2118802082","doi":"https://doi.org/10.1109/iccv.2009.5459261","mag":"2118802082"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2009.5459261","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2009.5459261","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE 12th International Conference on Computer Vision","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085640376","display_name":"Dorit S. Hochbaum","orcid":"https://orcid.org/0000-0002-2498-0512"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"D S Hochbaum","raw_affiliation_strings":["Haas School of Business, and Industrial Engineering and Operations Research, University of California, Berkeley, USA","Haas School of Business, and Industrial Eng. and Operations Research, Univ. of California, Berkeley, USA"],"affiliations":[{"raw_affiliation_string":"Haas School of Business, and Industrial Engineering and Operations Research, University of California, Berkeley, USA","institution_ids":["https://openalex.org/I95457486"]},{"raw_affiliation_string":"Haas School of Business, and Industrial Eng. and Operations Research, Univ. of California, Berkeley, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032996381","display_name":"Vijendra Singh","orcid":"https://orcid.org/0000-0001-5438-2188"},"institutions":[{"id":"https://openalex.org/I135310074","display_name":"University of Wisconsin\u2013Madison","ror":"https://ror.org/01y2jtd41","country_code":"US","type":"education","lineage":["https://openalex.org/I135310074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"V Singh","raw_affiliation_strings":["Biostatistics & Medical Informatics, and Computer Sciences, University of Wisconsin, Madison, USA","Biostatistics & Medical Informatics, and Computer Sciences, Univ. of Wisconsin-Madison, USA"],"affiliations":[{"raw_affiliation_string":"Biostatistics & Medical Informatics, and Computer Sciences, University of Wisconsin, Madison, USA","institution_ids":["https://openalex.org/I135310074"]},{"raw_affiliation_string":"Biostatistics & Medical Informatics, and Computer Sciences, Univ. of Wisconsin-Madison, USA","institution_ids":["https://openalex.org/I135310074"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5085640376"],"corresponding_institution_ids":["https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":17.0582,"has_fulltext":false,"cited_by_count":223,"citation_normalized_percentile":{"value":0.99371563,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"269","last_page":"276"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.7556463479995728},{"id":"https://openalex.org/keywords/cut","display_name":"Cut","score":0.7322874069213867},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6896535158157349},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.664535403251648},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6536577939987183},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6229652166366577},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5513029098510742},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5491072535514832},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5162999033927917},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4882981777191162},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4821745753288269},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4325951635837555},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3726418614387512},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3346686363220215},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.08902677893638611}],"concepts":[{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.7556463479995728},{"id":"https://openalex.org/C5134670","wikidata":"https://www.wikidata.org/wiki/Q1626444","display_name":"Cut","level":4,"score":0.7322874069213867},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6896535158157349},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.664535403251648},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6536577939987183},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6229652166366577},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5513029098510742},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5491072535514832},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5162999033927917},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4882981777191162},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4821745753288269},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4325951635837555},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3726418614387512},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3346686363220215},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.08902677893638611},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iccv.2009.5459261","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2009.5459261","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE 12th International Conference on Computer Vision","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.157.2445","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.157.2445","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.jhu.edu/~misha/ReadingSeminar/Papers/Hochbaum09.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1101550865","display_name":null,"funder_award_id":"DMI-0620677","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G1356839580","display_name":null,"funder_award_id":"CBET-0736232","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G266944840","display_name":null,"funder_award_id":"1UL1RR025011","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G4647189106","display_name":null,"funder_award_id":"UL1RR025011","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G5220373730","display_name":null,"funder_award_id":"1UL1RR02501","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G653087014","display_name":"ARI-LA: Domestic Nuclear Security Technology","funder_award_id":"0736232","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320316438","display_name":"Georgia Clinical and Translational Science Alliance","ror":null},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320333922","display_name":"Domestic Nuclear Detection Office","ror":"https://ror.org/01y5va805"},{"id":"https://openalex.org/F4320337390","display_name":"Division of Chemical, Bioengineering, Environmental, and Transport Systems","ror":"https://ror.org/0471zv972"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1572403558","https://openalex.org/W1579908337","https://openalex.org/W1964443764","https://openalex.org/W2006293258","https://openalex.org/W2013347084","https://openalex.org/W2020282424","https://openalex.org/W2029727948","https://openalex.org/W2038952578","https://openalex.org/W2096127742","https://openalex.org/W2109868644","https://openalex.org/W2120369594","https://openalex.org/W2129004009","https://openalex.org/W2129260071","https://openalex.org/W2132569499","https://openalex.org/W2134529554","https://openalex.org/W2143516773","https://openalex.org/W2147965279","https://openalex.org/W2156001867","https://openalex.org/W2157244733","https://openalex.org/W2171014688","https://openalex.org/W2171187077","https://openalex.org/W2171898823","https://openalex.org/W3147513489","https://openalex.org/W3169507310","https://openalex.org/W4249958705","https://openalex.org/W6634622082","https://openalex.org/W6679857762","https://openalex.org/W6684985541"],"related_works":["https://openalex.org/W2387690017","https://openalex.org/W2029983961","https://openalex.org/W4233585817","https://openalex.org/W2016045932","https://openalex.org/W2171149362","https://openalex.org/W1675950995","https://openalex.org/W2021544484","https://openalex.org/W2188882668","https://openalex.org/W2181395181","https://openalex.org/W2183780938"],"abstract_inverted_index":{"This":[0],"paper":[1],"is":[2,13,157],"focused":[3],"on":[4,93,184],"the":[5,11,27,46,49,56,77,85,94,101,119,122,134,150,160],"Co-segmentation":[6],"problem":[7,67],"[1]":[8,97],"-":[9,88],"where":[10],"objective":[12],"to":[14,113,118,149,159,174],"segment":[15],"a":[16,20,43,69,81,90,138,180],"similar":[17,158],"object":[18],"from":[19],"pair":[21,79],"of":[22,36,48,52,76,84,103,121,133],"images.":[23],"The":[24,127],"background":[25],"in":[26,55,137,163,168,176],"two":[28,50,86],"images":[29,38,58],"may":[30],"be":[31,40,172],"arbitrary;":[32],"therefore,":[33],"simultaneous":[34],"segmentation":[35,75],"both":[37],"must":[39],"performed":[41],"with":[42,80],"requirement":[44],"that":[45,143,169],"appearance":[47,96],"sets":[51],"foreground":[53,95],"pixels":[54],"respective":[57],"are":[59,108],"consistent.":[60],"Existing":[61],"approaches":[62],"[1,":[63],"2]":[64],"cast":[65],"this":[66,144],"as":[68],"Markov":[70],"Random":[71],"Field":[72],"(MRF)":[73],"based":[74],"image":[78],"regularized":[82],"difference":[83],"histograms":[87],"assuming":[89],"Gaussian":[91],"prior":[92],"or":[98],"by":[99],"calculating":[100],"sum":[102],"squared":[104],"differences":[105,136],"[2].":[106],"Both":[107],"interesting":[109],"formulations":[110],"but":[111,165],"lead":[112],"difficult":[114],"optimization":[115,152],"problems,":[116],"due":[117],"presence":[120],"second":[123],"(histogram":[124],"difference)":[125],"term.":[126],"model":[128],"proposed":[129],"here":[130],"bypasses":[131],"measurement":[132],"histogram":[135],"direct":[139],"fashion;":[140],"we":[141],"show":[142],"enables":[145],"obtaining":[146],"efficient":[147],"solutions":[148],"underlying":[151],"model.":[153],"Our":[154],"new":[155],"algorithm":[156],"existing":[161],"methods":[162],"spirit,":[164],"differs":[166],"substantially":[167],"it":[170],"can":[171],"solved":[173],"optimality":[175],"polynomial":[177],"time":[178],"using":[179],"maximum":[181],"flow":[182],"procedure":[183],"an":[185],"appropriately":[186],"constructed":[187],"graph.":[188],"We":[189],"discuss":[190],"our":[191],"ideas":[192],"and":[193],"present":[194],"promising":[195],"experimental":[196],"results.":[197]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":17},{"year":2018,"cited_by_count":21},{"year":2017,"cited_by_count":13},{"year":2016,"cited_by_count":26},{"year":2015,"cited_by_count":23},{"year":2014,"cited_by_count":18},{"year":2013,"cited_by_count":27},{"year":2012,"cited_by_count":24}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
