{"id":"https://openalex.org/W2120931403","doi":"https://doi.org/10.1109/cvprw.2006.18","title":"A Min-Cover Approach for Finding Salient Curves","display_name":"A Min-Cover Approach for Finding Salient Curves","publication_year":2006,"publication_date":"2006-07-10","ids":{"openalex":"https://openalex.org/W2120931403","doi":"https://doi.org/10.1109/cvprw.2006.18","mag":"2120931403"},"language":"en","primary_location":{"id":"doi:10.1109/cvprw.2006.18","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw.2006.18","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06)","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":"P. 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":"last","author":{"id":"https://openalex.org/A5033089246","display_name":"David McAllester","orcid":null},"institutions":[{"id":"https://openalex.org/I160992636","display_name":"Toyota Technological Institute at Chicago","ror":"https://ror.org/02sn5gb64","country_code":"US","type":"education","lineage":["https://openalex.org/I160992636"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"D. McAllester","raw_affiliation_strings":["TTI-Chicago","TTI at Chicago#TAB#"],"affiliations":[{"raw_affiliation_string":"TTI-Chicago","institution_ids":["https://openalex.org/I160992636"]},{"raw_affiliation_string":"TTI at Chicago#TAB#","institution_ids":["https://openalex.org/I160992636"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5023765219"],"corresponding_institution_ids":["https://openalex.org/I40347166"],"apc_list":null,"apc_paid":null,"fwci":4.4255,"has_fulltext":false,"cited_by_count":73,"citation_normalized_percentile":{"value":0.95069337,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"185","last_page":"185"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.9965999722480774,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9965999722480774,"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":0.9861999750137329,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9668999910354614,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/cover","display_name":"Cover (algebra)","score":0.6645398736000061},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6030473113059998},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5500270128250122},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5470519661903381},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5468723773956299},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.5455290079116821},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5407208800315857},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.517869234085083},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5160231590270996},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5138978958129883},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.4851742386817932},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4776400625705719},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.46578162908554077},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.44813072681427},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4329224228858948},{"id":"https://openalex.org/keywords/binary-image","display_name":"Binary image","score":0.4206621050834656},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3960086405277252},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.3363713026046753},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2349856197834015}],"concepts":[{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.6645398736000061},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6030473113059998},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5500270128250122},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5470519661903381},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5468723773956299},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.5455290079116821},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5407208800315857},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.517869234085083},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5160231590270996},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5138978958129883},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.4851742386817932},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4776400625705719},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.46578162908554077},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.44813072681427},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4329224228858948},{"id":"https://openalex.org/C193828747","wikidata":"https://www.wikidata.org/wiki/Q864118","display_name":"Binary image","level":4,"score":0.4206621050834656},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3960086405277252},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3363713026046753},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2349856197834015},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cvprw.2006.18","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw.2006.18","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.66.3186","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.66.3186","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://people.cs.uchicago.edu/~pff/papers/curves.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1496659931","https://openalex.org/W1518654683","https://openalex.org/W1558012644","https://openalex.org/W1562494114","https://openalex.org/W1866987313","https://openalex.org/W1992336406","https://openalex.org/W2111692787","https://openalex.org/W2113656553","https://openalex.org/W2117740473","https://openalex.org/W2119823327","https://openalex.org/W2128197592","https://openalex.org/W2128439793","https://openalex.org/W2129104643","https://openalex.org/W2133267925","https://openalex.org/W2140966579","https://openalex.org/W2142707712","https://openalex.org/W2154791445","https://openalex.org/W2159071715","https://openalex.org/W2787704407","https://openalex.org/W6633685643","https://openalex.org/W6639147146","https://openalex.org/W6648274853","https://openalex.org/W6679372278","https://openalex.org/W6682519532","https://openalex.org/W6748092013"],"related_works":["https://openalex.org/W2329500892","https://openalex.org/W2116510815","https://openalex.org/W2373164917","https://openalex.org/W2140201873","https://openalex.org/W2372440138","https://openalex.org/W264606855","https://openalex.org/W2380599080","https://openalex.org/W2018310142","https://openalex.org/W2359120553","https://openalex.org/W4210660906"],"abstract_inverted_index":{"We":[0,72,153],"consider":[1],"the":[2,43,61,79,118,136,156,172],"problem":[3,22,97],"of":[4,9,14,18,51,66,70,81,120,127],"deriving":[5],"a":[6,15,26,48,52,67,74,87,103,112,125],"global":[7],"interpretation":[8],"an":[10],"image":[11,63,142],"in":[12,64,164],"terms":[13,65],"small":[16,68],"set":[17,69],"smooth":[19],"curves.":[20,33],"The":[21,95,139],"is":[23,47,91,98,102],"posed":[24],"using":[25,86,171],"statistical":[27],"model":[28],"for":[29,77,135,160],"images":[30],"with":[31,83],"multiple":[32,84],"Besides":[34],"having":[35],"important":[36],"applications":[37],"to":[38,59,130],"edge":[39],"detection":[40,122,158],"and":[41,93,167],"grouping":[42],"curve":[44,121,157],"finding":[45,161],"task":[46],"special":[49],"case":[50,119],"more":[53],"general":[54],"problem,":[55],"where":[56],"we":[57,123],"want":[58],"explain":[60],"whole":[62],"objects.":[71],"describe":[73],"novel":[75],"approach":[76],"estimating":[78],"content":[80],"scenes":[82,166],"objects":[85,110],"min-cover":[88,96],"framework":[89],"that":[90,107],"simple":[92],"powerful.":[94],"NP-hard":[99],"but":[100],"there":[101],"good":[104,133],"approximation":[105],"algorithm":[106],"sequentially":[108],"selects":[109],"minimizing":[111],"\"cost":[113],"per":[114],"pixel\"":[115],"measure.":[116],"In":[117],"use":[124],"type":[126],"best-first":[128],"search":[129],"quickly":[131],"find":[132],"curves":[134,146],"covering":[137],"algorithm.":[138],"method":[140,159],"integrates":[141],"data":[143],"over":[144],"long":[145],"without":[147],"relying":[148],"on":[149],"binary":[150],"feature":[151],"detection.":[152],"have":[154],"applied":[155],"object":[162],"boundaries":[163],"natural":[165],"measured":[168],"its":[169],"performance":[170],"Berkeley":[173],"segmentation":[174],"dataset.":[175]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":8},{"year":2013,"cited_by_count":9},{"year":2012,"cited_by_count":8}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}