{"id":"https://openalex.org/W2018006179","doi":"https://doi.org/10.1109/cvpr.2012.6248021","title":"Multi-attribute spaces: Calibration for attribute fusion and similarity search","display_name":"Multi-attribute spaces: Calibration for attribute fusion and similarity search","publication_year":2012,"publication_date":"2012-06-01","ids":{"openalex":"https://openalex.org/W2018006179","doi":"https://doi.org/10.1109/cvpr.2012.6248021","mag":"2018006179"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2012.6248021","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2012.6248021","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE 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/A5091513740","display_name":"Walter J. Scheirer","orcid":"https://orcid.org/0000-0001-9649-8074"},"institutions":[{"id":"https://openalex.org/I888729015","display_name":"University of Colorado Colorado Springs","ror":"https://ror.org/054spjc55","country_code":"US","type":"education","lineage":["https://openalex.org/I888729015"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"W. J. Scheirer","raw_affiliation_strings":["Securics, Inc., USA","University of Colorado at Colorado, Springs"],"affiliations":[{"raw_affiliation_string":"Securics, Inc., USA","institution_ids":[]},{"raw_affiliation_string":"University of Colorado at Colorado, Springs","institution_ids":["https://openalex.org/I888729015"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101870263","display_name":"Neeraj Kumar","orcid":"https://orcid.org/0009-0000-7557-1084"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"N. Kumar","raw_affiliation_strings":["University of Washington, USA","University of Washington"],"affiliations":[{"raw_affiliation_string":"University of Washington, USA","institution_ids":["https://openalex.org/I201448701"]},{"raw_affiliation_string":"University of Washington","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002881666","display_name":"Peter N. Belhumeur","orcid":null},"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":"P. N. Belhumeur","raw_affiliation_strings":["Columbia University, USA","Columbia University"],"affiliations":[{"raw_affiliation_string":"Columbia University, USA","institution_ids":["https://openalex.org/I78577930"]},{"raw_affiliation_string":"Columbia University","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111521114","display_name":"T.E. Boult","orcid":null},"institutions":[{"id":"https://openalex.org/I888729015","display_name":"University of Colorado Colorado Springs","ror":"https://ror.org/054spjc55","country_code":"US","type":"education","lineage":["https://openalex.org/I888729015"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"T. E. Boult","raw_affiliation_strings":["Securics, Inc., USA","University of Colorado at Colorado, Springs"],"affiliations":[{"raw_affiliation_string":"Securics, Inc., USA","institution_ids":[]},{"raw_affiliation_string":"University of Colorado at Colorado, Springs","institution_ids":["https://openalex.org/I888729015"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5091513740"],"corresponding_institution_ids":["https://openalex.org/I888729015"],"apc_list":null,"apc_paid":null,"fwci":24.7158,"has_fulltext":false,"cited_by_count":178,"citation_normalized_percentile":{"value":0.99674209,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9983999729156494,"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/T10057","display_name":"Face and Expression Recognition","score":0.9983999729156494,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9957000017166138,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.994700014591217,"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":0.7167341113090515},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6046971082687378},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.5721065402030945},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5610586404800415},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.559394896030426},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5362071394920349},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4333687424659729},{"id":"https://openalex.org/keywords/attribute-domain","display_name":"Attribute domain","score":0.4291585683822632},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.4243358075618744},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3689415454864502},{"id":"https://openalex.org/keywords/rough-set","display_name":"Rough set","score":0.23648542165756226},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.21424683928489685}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7167341113090515},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6046971082687378},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.5721065402030945},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5610586404800415},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.559394896030426},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5362071394920349},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4333687424659729},{"id":"https://openalex.org/C75814411","wikidata":"https://www.wikidata.org/wiki/Q4818714","display_name":"Attribute domain","level":3,"score":0.4291585683822632},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.4243358075618744},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3689415454864502},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.23648542165756226},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21424683928489685},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr.2012.6248021","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2012.6248021","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1528802670","https://openalex.org/W1584193343","https://openalex.org/W1599238028","https://openalex.org/W1998197760","https://openalex.org/W2008297189","https://openalex.org/W2012955513","https://openalex.org/W2057818700","https://openalex.org/W2066134726","https://openalex.org/W2084435358","https://openalex.org/W2085660690","https://openalex.org/W2098411764","https://openalex.org/W2100332042","https://openalex.org/W2104850029","https://openalex.org/W2123126017","https://openalex.org/W2123460005","https://openalex.org/W2125560515","https://openalex.org/W2126448884","https://openalex.org/W2151509460","https://openalex.org/W2159543502","https://openalex.org/W2294130536","https://openalex.org/W3143107425","https://openalex.org/W6631694491","https://openalex.org/W6634846276","https://openalex.org/W6635793669","https://openalex.org/W6678412313","https://openalex.org/W6678800043"],"related_works":["https://openalex.org/W2953716828","https://openalex.org/W2904857019","https://openalex.org/W2944728705","https://openalex.org/W3011538607","https://openalex.org/W2904022177","https://openalex.org/W2591697403","https://openalex.org/W4321441197","https://openalex.org/W2359348847","https://openalex.org/W4294432981","https://openalex.org/W2347574505"],"abstract_inverted_index":{"Recent":[0],"work":[1],"has":[2],"shown":[3],"that":[4,94,135,178],"visual":[5],"attributes":[6,56],"are":[7],"a":[8,36,48,92,112,158],"powerful":[9],"approach":[10,133],"for":[11,54],"applications":[12],"such":[13],"as":[14,26,121,123],"recognition,":[15],"image":[16],"description":[17],"and":[18,168],"retrieval.":[19],"However,":[20],"fusing":[21],"multiple":[22],"attribute":[23,42,97,146,152],"scores":[24],"-":[25,34],"required":[27],"during":[28],"multi-attribute":[29],"queries":[30],"or":[31],"similarity":[32,126,180],"searches":[33],"presents":[35],"significant":[37,129,170],"challenge.":[38],"Scores":[39],"from":[40,72],"different":[41,55,59],"classifiers":[43],"cannot":[44],"be":[45,109],"combined":[46],"in":[47,100,111],"simple":[49,113],"way;":[50],"the":[51,80,95,101,136,145],"same":[52],"score":[53,90],"can":[57,108],"mean":[58],"things.":[60],"In":[61],"this":[62],"work,":[63],"we":[64],"show":[65,169,177],"how":[66,105],"to":[67,91,115,144],"construct":[68],"normalized":[69],"\u201cmulti-attribute":[70],"spaces\u201d":[71],"raw":[73,89],"classifier":[74],"outputs,":[75],"using":[76,186],"techniques":[77],"based":[78],"on":[79,157],"statistical":[81],"Extreme":[82],"Value":[83],"Theory.":[84],"Our":[85],"method":[86],"calibrates":[87],"each":[88],"probability":[93],"given":[96],"is":[98,134,138],"present":[99],"image.":[102],"We":[103,154,175],"describe":[104],"these":[106],"probabilities":[107],"fused":[110],"way":[114],"perform":[116],"more":[117],"accurate":[118],"multiattribute":[119],"searches,":[120],"well":[122],"enable":[124],"attribute-based":[125],"searches.":[127],"A":[128],"advantage":[130],"of":[131,162,181],"our":[132],"normalization":[137],"done":[139],"after-the-fact,":[140],"requiring":[141],"neither":[142],"modification":[143],"classification":[147],"system":[148],"nor":[149],"ground":[150],"truth":[151],"annotations.":[153],"demonstrate":[155],"results":[156,183],"large":[159],"data":[160],"set":[161],"nearly":[163],"2":[164],"million":[165],"face":[166],"images":[167],"improvements":[171],"over":[172],"prior":[173],"work.":[174],"also":[176],"perceptual":[179],"search":[182],"increases":[184],"by":[185],"contextual":[187],"attributes.":[188]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":29},{"year":2016,"cited_by_count":21},{"year":2015,"cited_by_count":31},{"year":2014,"cited_by_count":32},{"year":2013,"cited_by_count":23},{"year":2012,"cited_by_count":3}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}