{"id":"https://openalex.org/W2065054005","doi":"https://doi.org/10.1109/icip.2014.7026009","title":"Biometrics on visual preferences: A &amp;#x201C;pump and distill&amp;#x201D; regression approach","display_name":"Biometrics on visual preferences: A &amp;#x201C;pump and distill&amp;#x201D; regression approach","publication_year":2014,"publication_date":"2014-10-01","ids":{"openalex":"https://openalex.org/W2065054005","doi":"https://doi.org/10.1109/icip.2014.7026009","mag":"2065054005"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2014.7026009","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2014.7026009","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Image Processing (ICIP)","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/A5085430564","display_name":"Cristina Segalin","orcid":"https://orcid.org/0000-0001-7219-7074"},"institutions":[{"id":"https://openalex.org/I119439378","display_name":"University of Verona","ror":"https://ror.org/039bp8j42","country_code":"IT","type":"education","lineage":["https://openalex.org/I119439378"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"C. Segalin","raw_affiliation_strings":["University of Verona, Italy"],"affiliations":[{"raw_affiliation_string":"University of Verona, Italy","institution_ids":["https://openalex.org/I119439378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108685730","display_name":"Alessandro Perina","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I30771326","display_name":"Italian Institute of Technology","ror":"https://ror.org/042t93s57","country_code":"IT","type":"facility","lineage":["https://openalex.org/I30771326"]}],"countries":["IT","US"],"is_corresponding":false,"raw_author_name":"A. Perina","raw_affiliation_strings":["Istituto Italiano di Tecnologia (IIT), Genova, Italy","Microsoft Research, Redmond, WA"],"affiliations":[{"raw_affiliation_string":"Istituto Italiano di Tecnologia (IIT), Genova, Italy","institution_ids":["https://openalex.org/I30771326"]},{"raw_affiliation_string":"Microsoft Research, Redmond, WA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033671063","display_name":"Marco Cristani","orcid":"https://orcid.org/0000-0002-0523-6042"},"institutions":[{"id":"https://openalex.org/I119439378","display_name":"University of Verona","ror":"https://ror.org/039bp8j42","country_code":"IT","type":"education","lineage":["https://openalex.org/I119439378"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"M. Cristani","raw_affiliation_strings":["University of Verona, Italy"],"affiliations":[{"raw_affiliation_string":"University of Verona, Italy","institution_ids":["https://openalex.org/I119439378"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5085430564"],"corresponding_institution_ids":["https://openalex.org/I119439378"],"apc_list":null,"apc_paid":null,"fwci":0.4877,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.69830574,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"4982","last_page":"4986"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9922000169754028,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9922000169754028,"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/T11094","display_name":"Face Recognition and Perception","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9879000186920166,"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/biometrics","display_name":"Biometrics","score":0.8246155977249146},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6999963521957397},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6512452363967896},{"id":"https://openalex.org/keywords/authentication","display_name":"Authentication (law)","score":0.5900444388389587},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5332987308502197},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5215159058570862},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.49991512298583984},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4864318370819092},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.48076459765434265},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.4732647240161896},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39309945702552795},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39065584540367126},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.06486150622367859}],"concepts":[{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.8246155977249146},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6999963521957397},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6512452363967896},{"id":"https://openalex.org/C148417208","wikidata":"https://www.wikidata.org/wiki/Q4825882","display_name":"Authentication (law)","level":2,"score":0.5900444388389587},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5332987308502197},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5215159058570862},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.49991512298583984},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4864318370819092},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.48076459765434265},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.4732647240161896},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39309945702552795},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39065584540367126},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.06486150622367859},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2014.7026009","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2014.7026009","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W181985881","https://openalex.org/W1523682477","https://openalex.org/W1977470670","https://openalex.org/W2102773363","https://openalex.org/W2107995994","https://openalex.org/W2135046866","https://openalex.org/W2152395371","https://openalex.org/W2912934387","https://openalex.org/W4212883601"],"related_works":["https://openalex.org/W2076845124","https://openalex.org/W2183964146","https://openalex.org/W2379932303","https://openalex.org/W3147744369","https://openalex.org/W4241440711","https://openalex.org/W2062586268","https://openalex.org/W2019582947","https://openalex.org/W3212688212","https://openalex.org/W4300873085","https://openalex.org/W3104966193"],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2,21,29,51,73,87,97,114,121,140,152,159],"statistical":[3],"behavioural":[4],"biometric":[5],"approach":[6,55,128,162],"for":[7,25],"recognizing":[8],"people":[9],"by":[10,50,70],"their":[11],"aesthetic":[12],"preferences,":[13],"using":[14,28],"colour":[15],"images.":[16,34],"In":[17,35,78,149],"the":[18,36,62,79,109,130,161,184,187],"enrollment":[19],"phase,":[20,38],"model":[22,40],"is":[23,41,56,68,84,104],"learnt":[24],"each":[26,66,82],"user,":[27,123,160],"training":[30,63],"set":[31,46,64,74,88],"of":[32,47,65,75,89,94,142,154,158,169,176,180,186],"preferred":[33,49,156],"recognition/authentication":[37],"such":[39],"tested":[42],"with":[43,166],"an":[44,167,173],"unseen":[45],"pictures":[48],"probe":[52],"subject.":[53],"The":[54,127],"dubbed":[57],"\u201cpump":[58],"and":[59,134,146,171,189],"distill\u201d,":[60],"since":[61],"user":[67],"pumped":[69],"bagging,":[71],"producing":[72],"image":[76],"ensembles.":[77],"distill":[80],"step,":[81],"ensemble":[83],"reduced":[85],"into":[86],"surrogates,":[90],"that":[91],"is,":[92],"aggregates":[93],"images":[95,118,145,157],"sharing":[96],"similar":[98],"visual":[99],"content.":[100],"Finally,":[101],"LASSO":[102],"regression":[103],"performed":[105],"on":[106,132,139],"these":[107],"surrogates;":[108],"resulting":[110],"regressor,":[111],"employed":[112],"as":[113],"classifier,":[115],"takes":[116],"test":[117],"belonging":[119],"to":[120],"single":[122],"predicting":[124],"his":[125,164],"identity.":[126],"improves":[129],"state-of-the-art":[131],"recognition":[133],"authentication":[135,174],"tasks":[136],"in":[137,178],"average,":[138],"dataset":[141],"40000":[143],"Flickr":[144],"200":[147],"users.":[148],"practice,":[150],"given":[151],"pool":[153],"20":[155],"recognizes":[163],"identity":[165],"accuracy":[168,175],"92%,":[170],"sets":[172],"91%":[177],"terms":[179],"normalized":[181],"Area":[182],"Under":[183],"Curve":[185],"CMC":[188],"ROC":[190],"curve,":[191],"respectively.":[192]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
