{"id":"https://openalex.org/W2090882560","doi":"https://doi.org/10.1109/cvpr.2010.5540077","title":"Globally optimal pixel labeling algorithms for tree metrics","display_name":"Globally optimal pixel labeling algorithms for tree metrics","publication_year":2010,"publication_date":"2010-06-01","ids":{"openalex":"https://openalex.org/W2090882560","doi":"https://doi.org/10.1109/cvpr.2010.5540077","mag":"2090882560"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2010.5540077","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2010.5540077","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","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/A5023765219","display_name":"Pedro F. Felzenszwalb","orcid":null},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Pedro F. Felzenszwalb","raw_affiliation_strings":["University of Chicago, USA","University-of Chicago"],"affiliations":[{"raw_affiliation_string":"University of Chicago, USA","institution_ids":["https://openalex.org/I40347166"]},{"raw_affiliation_string":"University-of Chicago","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077585544","display_name":"Gyula Pap","orcid":"https://orcid.org/0000-0002-1516-5567"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gyula Pap","raw_affiliation_strings":["Cornell University, USA","Cornell University"],"affiliations":[{"raw_affiliation_string":"Cornell University, USA","institution_ids":["https://openalex.org/I205783295"]},{"raw_affiliation_string":"Cornell University","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025175846","display_name":"\u00c9va Tardos","orcid":"https://orcid.org/0000-0002-2978-1475"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eva Tardos","raw_affiliation_strings":["Cornell University, USA","Cornell University"],"affiliations":[{"raw_affiliation_string":"Cornell University, USA","institution_ids":["https://openalex.org/I205783295"]},{"raw_affiliation_string":"Cornell University","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042850991","display_name":"Ramin Zabih","orcid":"https://orcid.org/0000-0001-8769-5666"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ramin Zabih","raw_affiliation_strings":["Cornell University, USA","Cornell University"],"affiliations":[{"raw_affiliation_string":"Cornell University, USA","institution_ids":["https://openalex.org/I205783295"]},{"raw_affiliation_string":"Cornell University","institution_ids":["https://openalex.org/I205783295"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5023765219"],"corresponding_institution_ids":["https://openalex.org/I40347166"],"apc_list":null,"apc_paid":null,"fwci":1.5936,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.84972786,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3153","last_page":"3160"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12923","display_name":"Digital Image Processing 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/T12923","display_name":"Digital Image Processing 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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9994000196456909,"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":0.996399998664856,"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/computer-science","display_name":"Computer science","score":0.7207695841789246},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.658379316329956},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6231018900871277},{"id":"https://openalex.org/keywords/cut","display_name":"Cut","score":0.5981428027153015},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5689185261726379},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5228386521339417},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5201647281646729},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4719259738922119},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46554598212242126},{"id":"https://openalex.org/keywords/colored","display_name":"Colored","score":0.4475564956665039},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44466885924339294},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4419049024581909},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.437456876039505},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2571200728416443},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.20888248085975647},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.10509830713272095}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7207695841789246},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.658379316329956},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6231018900871277},{"id":"https://openalex.org/C5134670","wikidata":"https://www.wikidata.org/wiki/Q1626444","display_name":"Cut","level":4,"score":0.5981428027153015},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5689185261726379},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5228386521339417},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5201647281646729},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4719259738922119},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46554598212242126},{"id":"https://openalex.org/C2778307483","wikidata":"https://www.wikidata.org/wiki/Q5149038","display_name":"Colored","level":2,"score":0.4475564956665039},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44466885924339294},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4419049024581909},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.437456876039505},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2571200728416443},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.20888248085975647},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.10509830713272095},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr.2010.5540077","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2010.5540077","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.7900000214576721,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W79315950","https://openalex.org/W1560512119","https://openalex.org/W1989650529","https://openalex.org/W1997866406","https://openalex.org/W2013347084","https://openalex.org/W2016381774","https://openalex.org/W2030536784","https://openalex.org/W2067191022","https://openalex.org/W2082165536","https://openalex.org/W2099330788","https://openalex.org/W2104094303","https://openalex.org/W2105352479","https://openalex.org/W2107884096","https://openalex.org/W2110593503","https://openalex.org/W2113137767","https://openalex.org/W2118825986","https://openalex.org/W2119823327","https://openalex.org/W2121392031","https://openalex.org/W2124351162","https://openalex.org/W2135705692","https://openalex.org/W2140502500","https://openalex.org/W2140789035","https://openalex.org/W2143516773","https://openalex.org/W2146036075","https://openalex.org/W2151398556","https://openalex.org/W2153980837","https://openalex.org/W2159080219","https://openalex.org/W2162366888","https://openalex.org/W2165949176","https://openalex.org/W2169551590","https://openalex.org/W2340006107","https://openalex.org/W2427881153","https://openalex.org/W6633434192","https://openalex.org/W6676015048"],"related_works":["https://openalex.org/W2375137989","https://openalex.org/W2010171670","https://openalex.org/W2109407305","https://openalex.org/W2032319136","https://openalex.org/W2897997384","https://openalex.org/W2088651901","https://openalex.org/W1544828638","https://openalex.org/W2086619084","https://openalex.org/W2000036183","https://openalex.org/W2049858394"],"abstract_inverted_index":{"We":[0,80],"consider":[1],"pixel":[2,95],"labeling":[3,96],"problems":[4,20,97],"where":[5,13],"the":[6,14,51,67,91,141,145],"label":[7,29,116],"set":[8],"forms":[9],"a":[10,26,40,105,133,153,162],"tree,":[11],"and":[12],"observations":[15],"are":[16],"also":[17],"labels.":[18],"Such":[19],"arise":[21],"in":[22,33,161],"feature-space":[23],"analysis":[24],"with":[25,98],"very":[27],"large":[28,115,126],"set,":[30],"for":[31,94,114],"instance":[32],"color":[34,159],"image":[35],"segmentation.":[36],"In":[37],"this":[38],"case":[39],"tree":[41,70,99],"of":[42,50,77,109,136,147],"labels":[43],"can":[44,156],"be":[45],"constructed":[46],"via":[47],"hierarchical":[48],"clustering":[49],"observations.":[52],"This":[53],"leads":[54],"to":[55,88,144],"an":[56],"obvious":[57],"distance":[58,65],"function":[59,93],"between":[60],"two":[61],"labels,":[62],"namely":[63],"their":[64],"within":[66],"tree;":[68],"such":[69],"metrics":[71],"have":[72],"been":[73],"extensively":[74],"studied":[75],"outside":[76],"computer":[78],"vision.":[79],"provide":[81],"fast":[82],"algorithms":[83],"that":[84,139],"use":[85],"graph":[86],"cuts":[87,124],"exactly":[89],"minimize":[90],"energy":[92],"metrics.":[100],"Our":[101,128],"work":[102],"substantially":[103],"improves":[104],"facility":[106],"location":[107],"algorithm":[108],"Kolen,":[110],"which":[111],"is":[112,132],"impractical":[113],"sets":[117],"L":[118],"since":[119],"it":[120],"requires":[121],"O(|L|)":[122],"min":[123,150],"on":[125],"graphs.":[127],"main":[129],"technical":[130],"contribution":[131],"new":[134],"ordering":[135],"swap":[137],"moves":[138],"reduces":[140],"running":[142],"time":[143],"equivalent":[146],"O(log":[148],"|L|)":[149],"cuts;":[151],"as":[152],"result,":[154],"we":[155],"handle":[157],"realistic-sized":[158],"images":[160],"few":[163],"seconds.":[164]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}