{"id":"https://openalex.org/W2153963165","doi":"https://doi.org/10.1109/cvpr.2003.1211451","title":"Object segmentation using graph cuts based active contours","display_name":"Object segmentation using graph cuts based active contours","publication_year":2005,"publication_date":"2005-04-12","ids":{"openalex":"https://openalex.org/W2153963165","doi":"https://doi.org/10.1109/cvpr.2003.1211451","mag":"2153963165"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2003.1211451","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2003.1211451","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings.","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/A5113354555","display_name":"Ning Xu","orcid":"https://orcid.org/0000-0002-2554-4309"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ning Xu","raw_affiliation_strings":["Beckman Institute & ECE Department, University of Illinois, Urbana-Champaign, IL, USA"],"affiliations":[{"raw_affiliation_string":"Beckman Institute & ECE Department, University of Illinois, Urbana-Champaign, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101811051","display_name":"Ravi Bansal","orcid":"https://orcid.org/0000-0002-8913-6021"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"R. Bansal","raw_affiliation_strings":["Department of Psychiatry, Columbia University, New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Psychiatry, Columbia University, New York, NY, USA","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108521995","display_name":"Narendra Ahuja","orcid":null},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"N. Ahuja","raw_affiliation_strings":["Beckman Institute & ECE Department, University of Illinois, Urbana-Champaign, IL, USA"],"affiliations":[{"raw_affiliation_string":"Beckman Institute & ECE Department, University of Illinois, Urbana-Champaign, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5113354555"],"corresponding_institution_ids":["https://openalex.org/I157725225"],"apc_list":null,"apc_paid":null,"fwci":8.8125,"has_fulltext":false,"cited_by_count":91,"citation_normalized_percentile":{"value":0.98182573,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"2","issue":null,"first_page":"II","last_page":"46"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation 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/T10052","display_name":"Medical Image Segmentation 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/T10531","display_name":"Advanced Vision and Imaging","score":0.9966999888420105,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9959999918937683,"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/maxima-and-minima","display_name":"Maxima and minima","score":0.7775039672851562},{"id":"https://openalex.org/keywords/cut","display_name":"Cut","score":0.7500149011611938},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6505131721496582},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6419894099235535},{"id":"https://openalex.org/keywords/active-contour-model","display_name":"Active contour model","score":0.6235445737838745},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5343806743621826},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5198836326599121},{"id":"https://openalex.org/keywords/jump","display_name":"Jump","score":0.5175384879112244},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5134986042976379},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4959753453731537},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.41550254821777344},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3434869050979614},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30893635749816895},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.19807371497154236}],"concepts":[{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.7775039672851562},{"id":"https://openalex.org/C5134670","wikidata":"https://www.wikidata.org/wiki/Q1626444","display_name":"Cut","level":4,"score":0.7500149011611938},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6505131721496582},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6419894099235535},{"id":"https://openalex.org/C112353826","wikidata":"https://www.wikidata.org/wiki/Q127313","display_name":"Active contour model","level":4,"score":0.6235445737838745},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5343806743621826},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5198836326599121},{"id":"https://openalex.org/C2780695682","wikidata":"https://www.wikidata.org/wiki/Q4005959","display_name":"Jump","level":2,"score":0.5175384879112244},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5134986042976379},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4959753453731537},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.41550254821777344},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3434869050979614},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30893635749816895},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.19807371497154236},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr.2003.1211451","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2003.1211451","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8899999856948853}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1508960934","https://openalex.org/W1907897951","https://openalex.org/W1964119857","https://openalex.org/W1977545325","https://openalex.org/W1991113069","https://openalex.org/W2086921140","https://openalex.org/W2101309634","https://openalex.org/W2102344476","https://openalex.org/W2104095591","https://openalex.org/W2109407305","https://openalex.org/W2113137767","https://openalex.org/W2120940390","https://openalex.org/W2120977599","https://openalex.org/W2121947440","https://openalex.org/W2131910503","https://openalex.org/W2132603077","https://openalex.org/W2134820502","https://openalex.org/W2136706845","https://openalex.org/W2142926463","https://openalex.org/W2145803225","https://openalex.org/W2149184914","https://openalex.org/W2153980837","https://openalex.org/W2169551590","https://openalex.org/W2576483540","https://openalex.org/W2752885492","https://openalex.org/W2998023265","https://openalex.org/W3211330693","https://openalex.org/W4251321576","https://openalex.org/W6674950339","https://openalex.org/W6677945368","https://openalex.org/W6681380224"],"related_works":["https://openalex.org/W4210537690","https://openalex.org/W2885157826","https://openalex.org/W1576780264","https://openalex.org/W1979702773","https://openalex.org/W2159463658","https://openalex.org/W2109407305","https://openalex.org/W2032319136","https://openalex.org/W2167523060","https://openalex.org/W2897997384","https://openalex.org/W2078152361"],"abstract_inverted_index":{"In":[0,132],"this":[1],"paper":[2],"we":[3],"present":[4],"a":[5,20,68],"graph":[6,30,43],"cuts":[7,31,44,74],"based":[8],"active":[9,23,37],"contours":[10,24,38,81],"(GCBAC)":[11],"approach":[12,120],"to":[13,45,61,79,101,123,144],"object":[14],"segmentation":[15,125],"problems.":[16,88],"Our":[17,119],"method":[18],"is":[19,94,105,115,136,142],"combination":[21],"of":[22,29,83,113,126],"and":[25,32,66,77,85,109,128,141,149],"the":[26,48,53,59,90,103,111,124,134],"optimization":[27],"tool":[28],"differs":[33],"fundamentally":[34],"from":[35],"traditional":[36,98],"in":[39,97],"that":[40],"it":[41,51],"uses":[42],"iteratively":[46],"deform":[47],"contour.":[49],"Consequently,":[50],"has":[52,58],"following":[54],"advantages.":[55],"(1)":[56],"It":[57],"ability":[60],"jump":[62],"over":[63],"local":[64],"minima":[65],"provide":[67],"more":[69],"global":[70],"result.":[71],"(2)":[72],"Graph":[73],"guarantee":[75],"continuity":[76],"lead":[78],"smooth":[80],"free":[82],"self-crossing":[84],"uneven":[86],"spacing":[87],"Therefore,":[89],"internal":[91],"force,":[92],"which":[93],"commonly":[95],"used":[96],"energy":[99],"functions":[100],"control":[102],"smoothness,":[104],"no":[106],"longer":[107],"needed,":[108],"hence":[110],"number":[112],"parameters":[114],"greatly":[116],"reduced.":[117],"(3).":[118],"easily":[121],"extends":[122],"three":[127],"higher":[129],"dimensional":[130],"objects.":[131],"addition,":[133],"algorithm":[135],"suitable":[137],"for":[138],"interactive":[139],"correction":[140],"shown":[143],"always":[145],"converge.":[146],"Experimental":[147],"results":[148],"analyses":[150],"are":[151],"provided.":[152]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":5},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":10}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}