{"id":"https://openalex.org/W1595891186","doi":"https://doi.org/10.1109/icb.2015.7139114","title":"Combining view-based pose normalization and feature transform for cross-pose face recognition","display_name":"Combining view-based pose normalization and feature transform for cross-pose face recognition","publication_year":2015,"publication_date":"2015-05-01","ids":{"openalex":"https://openalex.org/W1595891186","doi":"https://doi.org/10.1109/icb.2015.7139114","mag":"1595891186"},"language":"en","primary_location":{"id":"doi:10.1109/icb.2015.7139114","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icb.2015.7139114","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Biometrics (ICB)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100688045","display_name":"Hua Gao","orcid":"https://orcid.org/0000-0002-4078-3527"},"institutions":[{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Hua Gao","raw_affiliation_strings":["Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), Lausanne, Switzerland","\u00c9cole Polyt\u00e9chnique F\u00e9d\u00e9rale de Lausanne (EPFL), Switzerland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL), Lausanne, Switzerland","institution_ids":["https://openalex.org/I5124864"]},{"raw_affiliation_string":"\u00c9cole Polyt\u00e9chnique F\u00e9d\u00e9rale de Lausanne (EPFL), Switzerland","institution_ids":["https://openalex.org/I5124864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009982931","display_name":"Haz\u0131m Kemal Ekenel","orcid":"https://orcid.org/0000-0003-3697-8548"},"institutions":[{"id":"https://openalex.org/I48912391","display_name":"Istanbul Technical University","ror":"https://ror.org/059636586","country_code":"TR","type":"education","lineage":["https://openalex.org/I48912391"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Hazim Kemal Ekenel","raw_affiliation_strings":["Istanbul Technical University (ITU), Istanbul, Turkey","Istanbul Technical University ITU, Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Istanbul Technical University (ITU), Istanbul, Turkey","institution_ids":["https://openalex.org/I48912391"]},{"raw_affiliation_string":"Istanbul Technical University ITU, Turkey","institution_ids":["https://openalex.org/I48912391"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087051920","display_name":"Rainer Stiefelhagen","orcid":"https://orcid.org/0000-0001-8046-4945"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Rainer Stiefelhagen","raw_affiliation_strings":["Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany","Karlsruhe Institute of Technology (KIT),Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany","institution_ids":["https://openalex.org/I102335020"]},{"raw_affiliation_string":"Karlsruhe Institute of Technology (KIT),Germany","institution_ids":["https://openalex.org/I102335020"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"21","issue":null,"first_page":"487","last_page":"492"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9997000098228455,"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":0.9997000098228455,"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/T11448","display_name":"Face recognition and analysis","score":0.9995999932289124,"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/T10828","display_name":"Biometric Identification and Security","score":0.9909999966621399,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8368731737136841},{"id":"https://openalex.org/keywords/image-warping","display_name":"Image warping","score":0.7603654265403748},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.7518771886825562},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.7420540452003479},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.644882082939148},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6271295547485352},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6174612641334534},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.5969825387001038},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5575046539306641},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5478935837745667},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.5322574973106384},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.494476318359375},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.47472748160362244}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8368731737136841},{"id":"https://openalex.org/C157202957","wikidata":"https://www.wikidata.org/wiki/Q1659609","display_name":"Image warping","level":2,"score":0.7603654265403748},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.7518771886825562},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.7420540452003479},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.644882082939148},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6271295547485352},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6174612641334534},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.5969825387001038},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5575046539306641},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5478935837745667},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.5322574973106384},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.494476318359375},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.47472748160362244},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icb.2015.7139114","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icb.2015.7139114","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Biometrics (ICB)","raw_type":"proceedings-article"},{"id":"pmh:oai:polen.itu.edu.tr:11527/36473","is_oa":false,"landing_page_url":"https://hdl.handle.net/11527/36473","pdf_url":null,"source":{"id":"https://openalex.org/S4306400460","display_name":"Istanbul Technical University Academic Open Archive (Istanbul Technical University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I48912391","host_organization_name":"Istanbul Technical University","host_organization_lineage":["https://openalex.org/I48912391"],"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":"Article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5299999713897705,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1578309724","https://openalex.org/W1628541567","https://openalex.org/W1821881293","https://openalex.org/W1989702938","https://openalex.org/W1997011019","https://openalex.org/W2001565863","https://openalex.org/W2030899956","https://openalex.org/W2044701250","https://openalex.org/W2047508432","https://openalex.org/W2068017064","https://openalex.org/W2068291909","https://openalex.org/W2078118580","https://openalex.org/W2082020538","https://openalex.org/W2090767496","https://openalex.org/W2117072267","https://openalex.org/W2137225583","https://openalex.org/W2154211011","https://openalex.org/W2160126058","https://openalex.org/W2162458225","https://openalex.org/W2165723227","https://openalex.org/W2912990735","https://openalex.org/W6634508152","https://openalex.org/W6636620952","https://openalex.org/W6662335928","https://openalex.org/W6677495702","https://openalex.org/W6680302564"],"related_works":["https://openalex.org/W4253893311","https://openalex.org/W3089306886","https://openalex.org/W2113785214","https://openalex.org/W2798721181","https://openalex.org/W3201205132","https://openalex.org/W4387967917","https://openalex.org/W4312694060","https://openalex.org/W4386075737","https://openalex.org/W4393563475","https://openalex.org/W4382141741"],"abstract_inverted_index":{"Automatic":[0],"face":[1,141],"recognition":[2],"across":[3],"large":[4],"pose":[5,26,62,80,116,128,145,167],"changes":[6],"is":[7,40,75,111,157,170],"still":[8],"a":[9,15,36,99],"challenging":[10],"problem.":[11],"Previous":[12],"solutions":[13],"apply":[14],"transform":[16,74,162],"in":[17,60,118,130],"image":[18,39,73],"space":[19,22],"or":[20,66],"feature":[21,29,32],"for":[23],"normalizing":[24],"the":[25,31,44,51,83,104,124,135,139,144,166],"mismatch.":[27],"For":[28],"transform,":[30],"vector":[33],"extracted":[34],"on":[35,72,138],"probe":[37,121],"facial":[38],"transferred":[41],"to":[42,77,90,113,159],"match":[43],"gallery":[45,119],"condition":[46],"with":[47],"regression":[48,52],"models.":[49],"Usually,":[50],"models":[53],"are":[54,64,147],"learned":[55],"from":[56,86],"paired":[57],"gallery-probe":[58],"conditions,":[59],"which":[61,102],"angles":[63,146],"known":[65],"accurately":[67],"estimated.":[68],"The":[69,109],"solution":[70],"based":[71],"able":[76,112],"handle":[78,114],"continuous":[79,115],"changes,":[81],"yet":[82],"approach":[84],"suffers":[85],"warping":[87],"artifacts":[88],"due":[89],"misalignment":[91],"and":[92,120],"self-occlusion.":[93],"In":[94],"this":[95],"work,":[96],"we":[97],"propose":[98],"novel":[100],"approach,":[101],"combines":[103],"advantage":[105],"of":[106,126],"both":[107],"methods.":[108],"algorithm":[110,137],"mismatch":[117],"set,":[122],"mitigating":[123],"impact":[125],"inaccurate":[127],"estimation":[129],"feature-transform-based":[131],"method.":[132],"We":[133],"evaluate":[134],"proposed":[136,155],"FERET":[140],"database,":[142],"where":[143],"roughly":[148],"annotated.":[149],"Experimental":[150],"results":[151],"show":[152],"that":[153],"our":[154],"method":[156],"superior":[158],"solely":[160],"image/feature":[161],"methods,":[163],"especially":[164],"when":[165],"angle":[168],"difference":[169],"large.":[171]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}