{"id":"https://openalex.org/W3004650248","doi":"https://doi.org/10.1109/icip40778.2020.9191251","title":"Unconstrained Periocular Recognition: Using Generative Deep Learning Frameworks for Attribute Normalization","display_name":"Unconstrained Periocular Recognition: Using Generative Deep Learning Frameworks for Attribute Normalization","publication_year":2020,"publication_date":"2020-09-30","ids":{"openalex":"https://openalex.org/W3004650248","doi":"https://doi.org/10.1109/icip40778.2020.9191251","mag":"3004650248"},"language":"en","primary_location":{"id":"doi:10.1109/icip40778.2020.9191251","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191251","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2002.03985","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026966525","display_name":"Luiz A. Zanlorensi","orcid":"https://orcid.org/0000-0003-2545-0588"},"institutions":[{"id":"https://openalex.org/I52418104","display_name":"Universidade Federal do Paran\u00e1","ror":"https://ror.org/05syd6y78","country_code":"BR","type":"education","lineage":["https://openalex.org/I52418104"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Luiz A. Zanlorensi","raw_affiliation_strings":["Department of Informatics, Federal University of Paran\u00e1, Curitiba, Brazil","Federal University of Parana,Department of Informatics,Curitiba,Brazil"],"affiliations":[{"raw_affiliation_string":"Department of Informatics, Federal University of Paran\u00e1, Curitiba, Brazil","institution_ids":["https://openalex.org/I52418104"]},{"raw_affiliation_string":"Federal University of Parana,Department of Informatics,Curitiba,Brazil","institution_ids":["https://openalex.org/I52418104"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090305015","display_name":"Hugo Proen\u00e7a","orcid":"https://orcid.org/0000-0003-2551-8570"},"institutions":[{"id":"https://openalex.org/I161321875","display_name":"University of Beira Interior","ror":"https://ror.org/03nf36p02","country_code":"PT","type":"education","lineage":["https://openalex.org/I161321875"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Hugo Proenca","raw_affiliation_strings":["Department of Informatics, University of Beira Interior, Covilh\u00e3, Portugal","University of Beira Interior,Department of Informatics,Covilh\u00e3,Portugal"],"affiliations":[{"raw_affiliation_string":"Department of Informatics, University of Beira Interior, Covilh\u00e3, Portugal","institution_ids":["https://openalex.org/I161321875"]},{"raw_affiliation_string":"University of Beira Interior,Department of Informatics,Covilh\u00e3,Portugal","institution_ids":["https://openalex.org/I161321875"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033489756","display_name":"David Menotti","orcid":"https://orcid.org/0000-0003-2430-2030"},"institutions":[{"id":"https://openalex.org/I52418104","display_name":"Universidade Federal do Paran\u00e1","ror":"https://ror.org/05syd6y78","country_code":"BR","type":"education","lineage":["https://openalex.org/I52418104"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"David Menotti","raw_affiliation_strings":["Department of Informatics, Federal University of Paran\u00e1, Curitiba, Brazil","Federal University of Parana,Department of Informatics,Curitiba,Brazil"],"affiliations":[{"raw_affiliation_string":"Department of Informatics, Federal University of Paran\u00e1, Curitiba, Brazil","institution_ids":["https://openalex.org/I52418104"]},{"raw_affiliation_string":"Federal University of Parana,Department of Informatics,Curitiba,Brazil","institution_ids":["https://openalex.org/I52418104"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5026966525"],"corresponding_institution_ids":["https://openalex.org/I52418104"],"apc_list":null,"apc_paid":null,"fwci":0.334,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.61382107,"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":"1361","last_page":"1365"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11438","display_name":"Retinal Imaging and Analysis","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12989","display_name":"Ocular Disorders and Treatments","score":0.9853000044822693,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11194","display_name":"Ocular Diseases and Beh\u00e7et\u2019s Syndrome","score":0.9815999865531921,"subfield":{"id":"https://openalex.org/subfields/2731","display_name":"Ophthalmology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.8752288818359375},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.777060866355896},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6948134899139404},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6550272703170776},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6343783140182495},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.6185059547424316},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.536550760269165},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.5325638055801392},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.51133793592453},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.48682087659835815},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4014439582824707}],"concepts":[{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.8752288818359375},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.777060866355896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6948134899139404},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6550272703170776},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6343783140182495},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.6185059547424316},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.536550760269165},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.5325638055801392},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.51133793592453},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.48682087659835815},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4014439582824707},{"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":5,"locations":[{"id":"doi:10.1109/icip40778.2020.9191251","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191251","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2002.03985","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2002.03985","pdf_url":"https://arxiv.org/pdf/2002.03985","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3004650248","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2002.03985v1","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2002.03985","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2002.03985","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"},{"id":"doi:10.17023/yj3m-hx07","is_oa":true,"landing_page_url":"https://doi.org/10.17023/yj3m-hx07","pdf_url":null,"source":{"id":"https://openalex.org/S7407051697","display_name":"IEEE RESOURCE CENTERS","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2002.03985","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2002.03985","pdf_url":"https://arxiv.org/pdf/2002.03985","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7699999809265137}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"},{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3004650248.pdf","grobid_xml":"https://content.openalex.org/works/W3004650248.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W1607979445","https://openalex.org/W2033291679","https://openalex.org/W2039051707","https://openalex.org/W2097290407","https://openalex.org/W2151103935","https://openalex.org/W2152690956","https://openalex.org/W2161969291","https://openalex.org/W2566390765","https://openalex.org/W2579578355","https://openalex.org/W2594223102","https://openalex.org/W2767420072","https://openalex.org/W2772196976","https://openalex.org/W2777427179","https://openalex.org/W2799457671","https://openalex.org/W2891520308","https://openalex.org/W2895743108","https://openalex.org/W2950974703","https://openalex.org/W2962770929","https://openalex.org/W2963626105","https://openalex.org/W2963767194","https://openalex.org/W2964118024","https://openalex.org/W2976865175","https://openalex.org/W6640963894","https://openalex.org/W6687506355","https://openalex.org/W6729939709","https://openalex.org/W6739139180","https://openalex.org/W6745206590","https://openalex.org/W6770240103","https://openalex.org/W6785710507"],"related_works":["https://openalex.org/W2617513412","https://openalex.org/W2901178729","https://openalex.org/W3035739915","https://openalex.org/W2889886255","https://openalex.org/W121219881","https://openalex.org/W3109011336","https://openalex.org/W2608823669","https://openalex.org/W2965954137","https://openalex.org/W2996289226","https://openalex.org/W2134348239","https://openalex.org/W2397152153","https://openalex.org/W3022398175","https://openalex.org/W3198009109","https://openalex.org/W2982519139","https://openalex.org/W3044711549","https://openalex.org/W3190693498","https://openalex.org/W2963814162","https://openalex.org/W3190223954","https://openalex.org/W3184742309","https://openalex.org/W2738760914"],"abstract_inverted_index":{"Ocular":[0],"biometric":[1],"systems":[2],"working":[3],"in":[4,52,140,147],"unconstrained":[5,121],"environments":[6],"usually":[7],"face":[8],"the":[9,17,23,26,46,49,76,83,93,99,110,135,153,162],"problem":[10],"of":[11,25,48,89,101,103,125,137,155],"small":[12],"within-class":[13],"compactness":[14],"caused":[15],"by":[16,128],"multiple":[18],"factors":[19],"that":[20,44,69],"jointly":[21],"degrade":[22],"quality":[24],"obtained":[27],"data.":[28],"In":[29],"this":[30],"work,":[31],"we":[32,91,115],"propose":[33],"an":[34],"attribute":[35,157],"normalization":[36,112,158],"strategy":[37,85],"based":[38],"on":[39],"deep":[40],"learning":[41],"generative":[42],"frameworks,":[43],"reduces":[45],"variability":[47],"samples":[50],"used":[51],"pairwise":[53],"comparisons,":[54],"without":[55],"reducing":[56],"their":[57],"discriminability.":[58],"The":[59],"proposed":[60,111],"method":[61],"can":[62],"be":[63],"seen":[64],"as":[65],"a":[66,117],"preprocessing":[67],"step":[68],"contributes":[70],"for":[71,120],"data":[72],"regularization":[73],"and":[74,95,151],"improves":[75],"recognition":[77,84,106,141,163],"accuracy,":[78],"being":[79],"fully":[80],"agnostic":[81],"to":[82,133,160],"used.":[86],"As":[87],"proof":[88],"concept,":[90],"consider":[92],"\u201ceyeglasses\u201d":[94],"\u201cgaze\u201d":[96],"factors,":[97],"comparing":[98],"levels":[100],"performance":[102],"five":[104],"different":[105,149],"methods":[107],"with/without":[108],"using":[109],"strategy.":[113],"Also,":[114],"introduce":[116],"new":[118],"dataset":[119],"periocular":[122],"recognition,":[123],"composed":[124],"images":[126],"acquired":[127],"mobile":[129],"devices,":[130],"particularly":[131],"suited":[132],"perceive":[134],"impact":[136],"\u201cwearing":[138],"eyeglasses\u201d":[139],"effectiveness.":[142],"Our":[143],"experiments":[144],"were":[145],"performed":[146],"two":[148],"datasets,":[150],"support":[152],"usefulness":[154],"our":[156],"scheme":[159],"improve":[161],"performance.":[164]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}