{"id":"https://openalex.org/W2170526016","doi":"https://doi.org/10.1109/wacv.2009.5403029","title":"A general framework for reconciling multiple weak segmentations of an image","display_name":"A general framework for reconciling multiple weak segmentations of an image","publication_year":2009,"publication_date":"2009-12-01","ids":{"openalex":"https://openalex.org/W2170526016","doi":"https://doi.org/10.1109/wacv.2009.5403029","mag":"2170526016"},"language":"en","primary_location":{"id":"doi:10.1109/wacv.2009.5403029","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv.2009.5403029","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 Workshop on Applications of Computer Vision (WACV)","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/A5077112143","display_name":"Soumya Ghosh","orcid":"https://orcid.org/0000-0001-8508-0641"},"institutions":[{"id":"https://openalex.org/I27804330","display_name":"Brown University","ror":"https://ror.org/05gq02987","country_code":"US","type":"education","lineage":["https://openalex.org/I27804330"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Soumya Ghosh","raw_affiliation_strings":["Department of Computer Science, Brown University, Providence, RI, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Brown University, Providence, RI, USA","institution_ids":["https://openalex.org/I27804330"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110629518","display_name":"Joseph J. Pfeiffer","orcid":null},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joseph J. Pfeiffer","raw_affiliation_strings":["Department of Computer Science, Purdue University, West Lafayette, IN, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110145100","display_name":"Jane Mulligan","orcid":null},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jane Mulligan","raw_affiliation_strings":["Department of Computer Science, University of Colorado, Boulder, CO, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Colorado, Boulder, CO, USA","institution_ids":["https://openalex.org/I188538660"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5077112143"],"corresponding_institution_ids":["https://openalex.org/I27804330"],"apc_list":null,"apc_paid":null,"fwci":1.6067,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.86844397,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"15","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9976000189781189,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9975000023841858,"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":0.6347064971923828},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5382333397865295},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4421711564064026},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42711877822875977}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6347064971923828},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5382333397865295},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4421711564064026},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42711877822875977}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/wacv.2009.5403029","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv.2009.5403029","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 Workshop on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.188.4115","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.188.4115","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.colorado.edu/%7Ejanem/pdf/Ghosh09WACV.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":31,"referenced_works":["https://openalex.org/W183401690","https://openalex.org/W1999478155","https://openalex.org/W2009685382","https://openalex.org/W2046025323","https://openalex.org/W2067191022","https://openalex.org/W2081293863","https://openalex.org/W2081313007","https://openalex.org/W2098777834","https://openalex.org/W2104125540","https://openalex.org/W2105960416","https://openalex.org/W2112301665","https://openalex.org/W2116810533","https://openalex.org/W2119823327","https://openalex.org/W2121189958","https://openalex.org/W2121927366","https://openalex.org/W2121947440","https://openalex.org/W2124146842","https://openalex.org/W2125310925","https://openalex.org/W2135029798","https://openalex.org/W2136405884","https://openalex.org/W2137901062","https://openalex.org/W2147224278","https://openalex.org/W2159408114","https://openalex.org/W2171096036","https://openalex.org/W2172174906","https://openalex.org/W2295256067","https://openalex.org/W4285719527","https://openalex.org/W6677945368","https://openalex.org/W6680012447","https://openalex.org/W6683108456","https://openalex.org/W6685190505"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398","https://openalex.org/W2775347418"],"abstract_inverted_index":{"Segmentation,":[0],"or":[1,85,124],"partitioning":[2],"images":[3,66],"into":[4],"internally":[5],"homogeneous":[6],"regions,":[7],"is":[8],"an":[9,27],"important":[10],"first":[11],"step":[12],"in":[13],"many":[14],"Computer":[15],"Vision":[16],"tasks.":[17],"In":[18],"this":[19],"paper,":[20],"we":[21],"attack":[22],"the":[23,43,134],"segmentation":[24,96,137],"problem":[25],"using":[26],"ensemble":[28],"of":[29,112],"low":[30],"cost":[31],"image":[32,95,114,136],"segmentations.":[33],"These":[34],"segmentations":[35,81,115],"are":[36,131],"reconciled":[37],"by":[38],"applying":[39],"recent":[40],"techniques":[41],"from":[42,82,117,125],"consensus":[44],"clustering":[45,119],"literature":[46],"which":[47],"exploit":[48],"a":[49],"Non-negative":[50],"Matrix":[51],"Factorization":[52],"(NMF)":[53],"framework.":[54],"We":[55,88],"describe":[56],"extensions":[57],"to":[58,76],"these":[59],"methods":[60],"that":[61,91],"scale":[62],"them":[63],"for":[64],"large":[65],"and":[67,78,100],"also":[68],"incorporate":[69],"smoothness":[70],"constraints.":[71],"This":[72],"framework":[73],"allows":[74],"us":[75],"uniformly":[77],"easily":[79],"combine":[80],"different":[83],"algorithms":[84,130],"feature":[86,122],"modalities.":[87],"then":[89],"demonstrate":[90],"popular":[92],"bottom":[93],"up":[94],"algorithms,":[97],"Mean":[98],"Shift":[99],"Efficient":[101],"Graph":[102],"Based":[103],"segmentation,":[104],"perform":[105],"no":[106],"better":[107],"than":[108],"our":[109],"simple":[110],"combination":[111],"multiple":[113],"derived":[116],"k-means":[118],"(of":[120],"various":[121],"spaces)":[123],"\u201cnaive\u201d":[126],"RGB":[127],"quantizations.":[128],"The":[129],"evaluated":[132],"on":[133],"Berkeley":[135],"dataset.":[138]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}