{"id":"https://openalex.org/W1486171644","doi":"https://doi.org/10.1109/icb.2015.7139097","title":"Large Margin Coupled Feature Learning for cross-modal face recognition","display_name":"Large Margin Coupled Feature Learning for cross-modal face recognition","publication_year":2015,"publication_date":"2015-05-01","ids":{"openalex":"https://openalex.org/W1486171644","doi":"https://doi.org/10.1109/icb.2015.7139097","mag":"1486171644"},"language":"en","primary_location":{"id":"doi:10.1109/icb.2015.7139097","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icb.2015.7139097","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":"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/A5033896100","display_name":"Yi Jin","orcid":"https://orcid.org/0000-0001-8408-3816"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yi Jin","raw_affiliation_strings":["Beijing Jiaotong University, Beijing, China","\u00a0Beijing Jiaotong University, China"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"\u00a0Beijing Jiaotong University, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100460385","display_name":"Jiwen Lu","orcid":"https://orcid.org/0000-0002-6121-5529"},"institutions":[{"id":"https://openalex.org/I4210108443","display_name":"Advanced Digital Sciences Center","ror":"https://ror.org/01xaqx887","country_code":"SG","type":"facility","lineage":["https://openalex.org/I4210108443"]},{"id":"https://openalex.org/I115228651","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09","country_code":"SG","type":"government","lineage":["https://openalex.org/I115228651"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Jiwen Lu","raw_affiliation_strings":["Advanced Digital Sciences Center, Singapore","[Advanced Digital Sciences Center, Singapore]"],"affiliations":[{"raw_affiliation_string":"Advanced Digital Sciences Center, Singapore","institution_ids":["https://openalex.org/I4210108443"]},{"raw_affiliation_string":"[Advanced Digital Sciences Center, Singapore]","institution_ids":["https://openalex.org/I115228651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112109951","display_name":"Qiuqi Ruan","orcid":"https://orcid.org/0000-0001-8107-7365"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiuqi Ruan","raw_affiliation_strings":["Beijing Jiaotong University, Beijing, China","\u00a0Beijing Jiaotong University, China"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"\u00a0Beijing Jiaotong University, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5033896100"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":1.841,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.89881411,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"36","issue":null,"first_page":"286","last_page":"292"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T10057","display_name":"Face and Expression Recognition","score":0.9991000294685364,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9894000291824341,"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/discriminative-model","display_name":"Discriminative model","score":0.8395665287971497},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8052816390991211},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7595071792602539},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.7519068717956543},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7349687814712524},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6515194177627563},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.64870285987854},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.6277172565460205},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6246547102928162},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.5962386727333069},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.592677652835846},{"id":"https://openalex.org/keywords/three-dimensional-face-recognition","display_name":"Three-dimensional face recognition","score":0.581486701965332},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5050056576728821},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.4469456374645233},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4347790777683258},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4328547716140747},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.3377349376678467},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.24996787309646606}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8395665287971497},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8052816390991211},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7595071792602539},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.7519068717956543},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7349687814712524},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6515194177627563},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.64870285987854},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6277172565460205},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6246547102928162},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.5962386727333069},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.592677652835846},{"id":"https://openalex.org/C88799230","wikidata":"https://www.wikidata.org/wiki/Q3398329","display_name":"Three-dimensional face recognition","level":5,"score":0.581486701965332},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5050056576728821},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.4469456374645233},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4347790777683258},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4328547716140747},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.3377349376678467},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.24996787309646606},{"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icb.2015.7139097","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icb.2015.7139097","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"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7799999713897705,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W38226588","https://openalex.org/W1523385540","https://openalex.org/W1538281814","https://openalex.org/W1562230821","https://openalex.org/W1975056068","https://openalex.org/W1999478721","https://openalex.org/W2005286252","https://openalex.org/W2030899956","https://openalex.org/W2033419168","https://openalex.org/W2034136097","https://openalex.org/W2048110836","https://openalex.org/W2056602228","https://openalex.org/W2071207147","https://openalex.org/W2085810284","https://openalex.org/W2097940622","https://openalex.org/W2100235303","https://openalex.org/W2100302316","https://openalex.org/W2108657626","https://openalex.org/W2120749805","https://openalex.org/W2120824855","https://openalex.org/W2131081720","https://openalex.org/W2131216994","https://openalex.org/W2136995369","https://openalex.org/W2140556441","https://openalex.org/W2141345255","https://openalex.org/W2149407554","https://openalex.org/W2149481809","https://openalex.org/W2151103935","https://openalex.org/W2152788298","https://openalex.org/W2153288431","https://openalex.org/W2158096215","https://openalex.org/W2162666105","https://openalex.org/W2163808566","https://openalex.org/W2163922914","https://openalex.org/W2164530430","https://openalex.org/W2167260591","https://openalex.org/W2184188583","https://openalex.org/W2232201864","https://openalex.org/W2255038316","https://openalex.org/W2294512729","https://openalex.org/W2295088417","https://openalex.org/W2612133093","https://openalex.org/W2652751060","https://openalex.org/W6601507811","https://openalex.org/W6631216910","https://openalex.org/W6633630069","https://openalex.org/W6675065350","https://openalex.org/W6677782685","https://openalex.org/W6678025836","https://openalex.org/W6679755939","https://openalex.org/W6681227110","https://openalex.org/W6683871219","https://openalex.org/W6684115544","https://openalex.org/W6684125387","https://openalex.org/W6686207219","https://openalex.org/W6687101057","https://openalex.org/W6692019673","https://openalex.org/W6697020685","https://openalex.org/W6737419347","https://openalex.org/W6739509182"],"related_works":["https://openalex.org/W3119773509","https://openalex.org/W3208297503","https://openalex.org/W2889153461","https://openalex.org/W2964117661","https://openalex.org/W4388405611","https://openalex.org/W325114128","https://openalex.org/W2619127353","https://openalex.org/W4206923589","https://openalex.org/W3034828634","https://openalex.org/W3014491775"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,58,130],"Large":[4],"Margin":[5],"Coupled":[6],"Feature":[7],"Learning":[8],"(LMCFL)":[9],"method":[10,61],"for":[11,35],"cross-modal":[12,27,142],"face":[13,28,36,65,79,89,102,106,116,123,143],"recognition,":[14],"which":[15,38],"recognizes":[16],"persons":[17],"from":[18,22,91,118],"facial":[19],"images":[20,80,90,117],"captured":[21],"different":[23,92,119,141],"modalities.":[24,93],"Most":[25],"previous":[26],"recognition":[29,144],"methods":[30],"utilize":[31],"hand-crafted":[32],"feature":[33,51],"descriptors":[34],"representation,":[37],"require":[39],"strong":[40],"prior":[41],"knowledge":[42],"to":[43,62],"engineer":[44],"and":[45,84,104,111,132,146],"cannot":[46],"exploit":[47],"data-adaptive":[48],"characteristics":[49],"in":[50,81,108,129],"extraction.":[52],"In":[53],"this":[54],"work,":[55],"we":[56],"propose":[57],"new":[59],"LMCFL":[60,95,136],"learn":[63],"coupled":[64],"representation":[66],"at":[67],"the":[68,75,85,98,113,147,151],"image":[69],"pixel":[70],"level":[71],"by":[72],"jointly":[73],"utilizing":[74],"discriminative":[76,122,131],"information":[77,87],"of":[78,88,115,153],"each":[82,109],"modality":[83],"correlation":[86,114],"Thus,":[94],"can":[96,125],"maximize":[97,112],"margin":[99],"between":[100],"positive":[101],"pairs":[103,107],"negative":[105],"modality,":[110],"modalities,":[120],"where":[121],"features":[124],"be":[126],"automatically":[127],"learned":[128],"data-driven":[133],"way.":[134],"Our":[135],"is":[137],"validated":[138],"on":[139],"two":[140],"applications,":[145],"experimental":[148],"results":[149],"demonstrate":[150],"effectiveness":[152],"our":[154],"proposed":[155],"approach.":[156]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}