{"id":"https://openalex.org/W2035475513","doi":"https://doi.org/10.1109/lsp.2012.2230257","title":"Linear Discriminant Regression Classification for Face Recognition","display_name":"Linear Discriminant Regression Classification for Face Recognition","publication_year":2012,"publication_date":"2012-12-03","ids":{"openalex":"https://openalex.org/W2035475513","doi":"https://doi.org/10.1109/lsp.2012.2230257","mag":"2035475513"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2012.2230257","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2012.2230257","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-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/A5113708507","display_name":"Shih\u2010Ming Huang","orcid":"https://orcid.org/0000-0002-5772-921X"},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Shih-Ming Huang","raw_affiliation_strings":["Institute of Computer and Communication Engineering, Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan","[Dept. of Electr. Eng., Nat. Cheng-Kung Univ., Tainan, Taiwan]"],"affiliations":[{"raw_affiliation_string":"Institute of Computer and Communication Engineering, Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]},{"raw_affiliation_string":"[Dept. of Electr. Eng., Nat. Cheng-Kung Univ., Tainan, Taiwan]","institution_ids":["https://openalex.org/I91807558"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086898047","display_name":"Jar\u2010Ferr Yang","orcid":"https://orcid.org/0000-0003-3024-5634"},"institutions":[{"id":"https://openalex.org/I91807558","display_name":"National Cheng Kung University","ror":"https://ror.org/01b8kcc49","country_code":"TW","type":"education","lineage":["https://openalex.org/I91807558"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jar-Ferr Yang","raw_affiliation_strings":["Institute of Computer and Communication Engineering, Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan","[Dept. of Electr. Eng., Nat. Cheng-Kung Univ., Tainan, Taiwan]"],"affiliations":[{"raw_affiliation_string":"Institute of Computer and Communication Engineering, Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan","institution_ids":["https://openalex.org/I91807558"]},{"raw_affiliation_string":"[Dept. of Electr. Eng., Nat. Cheng-Kung Univ., Tainan, Taiwan]","institution_ids":["https://openalex.org/I91807558"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5113708507"],"corresponding_institution_ids":["https://openalex.org/I91807558"],"apc_list":null,"apc_paid":null,"fwci":6.0401,"has_fulltext":false,"cited_by_count":77,"citation_normalized_percentile":{"value":0.96892924,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":100},"biblio":{"volume":"20","issue":"1","first_page":"91","last_page":"94"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","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/T10057","display_name":"Face and Expression Recognition","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/T11448","display_name":"Face recognition and analysis","score":0.9366000294685364,"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":0.9345999956130981,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.8182774782180786},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7616844177246094},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.7615466117858887},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6906285881996155},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5777824521064758},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5751210451126099},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.5487990975379944},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.4942593574523926},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.46879562735557556},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4602363109588623},{"id":"https://openalex.org/keywords/kernel-fisher-discriminant-analysis","display_name":"Kernel Fisher discriminant analysis","score":0.45514753460884094},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.43694204092025757},{"id":"https://openalex.org/keywords/scatter-matrix","display_name":"Scatter matrix","score":0.43437460064888},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3747096061706543},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.23867961764335632},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.2129499316215515},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.20879268646240234}],"concepts":[{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.8182774782180786},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7616844177246094},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.7615466117858887},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6906285881996155},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5777824521064758},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5751210451126099},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.5487990975379944},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.4942593574523926},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.46879562735557556},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4602363109588623},{"id":"https://openalex.org/C181367576","wikidata":"https://www.wikidata.org/wiki/Q6394184","display_name":"Kernel Fisher discriminant analysis","level":4,"score":0.45514753460884094},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.43694204092025757},{"id":"https://openalex.org/C176917957","wikidata":"https://www.wikidata.org/wiki/Q7430596","display_name":"Scatter matrix","level":4,"score":0.43437460064888},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3747096061706543},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.23867961764335632},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.2129499316215515},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.20879268646240234},{"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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"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/C180877172","wikidata":"https://www.wikidata.org/wiki/Q5401390","display_name":"Estimation of covariance matrices","level":3,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2012.2230257","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2012.2230257","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6800000071525574,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1989702938","https://openalex.org/W2014697905","https://openalex.org/W2033419168","https://openalex.org/W2045591889","https://openalex.org/W2097486709","https://openalex.org/W2121647436","https://openalex.org/W2146474141"],"related_works":["https://openalex.org/W2141981133","https://openalex.org/W1978302214","https://openalex.org/W1963649114","https://openalex.org/W3147024994","https://openalex.org/W2321869780","https://openalex.org/W2162393942","https://openalex.org/W2025089370","https://openalex.org/W2589829774","https://openalex.org/W1570195136","https://openalex.org/W2379730211"],"abstract_inverted_index":{"To":[0],"improve":[1],"the":[2,5,25,28,35,39,53,56,62,74,78,91,97,107,115,120],"robustness":[3],"of":[4,27,55],"linear":[6,17],"regression":[7,19,45,122],"classification":[8,20],"(LRC)":[9],"algorithm,":[10],"in":[11],"this":[12],"paper,":[13],"we":[14],"propose":[15],"a":[16,42,85,127],"discriminant":[18,44],"(LDRC)":[21],"algorithm":[22],"to":[23,51,67],"boost":[24],"effectiveness":[26],"LRC":[29,40,75,79,98],"for":[30,73,88,99,130],"face":[31,100,111,131],"recognition.":[32,101,132],"We":[33],"embed":[34],"Fisher":[36],"criterion":[37],"into":[38],"as":[41],"novel":[43],"analysis":[46],"method.":[47],"The":[48],"LDRC":[49,116],"attempts":[50],"maximize":[52],"ratio":[54],"between-class":[57],"reconstruction":[58,64],"error":[59,65],"(BCRE)":[60],"over":[61],"within-class":[63],"(WCRE)":[66],"find":[68],"an":[69],"optimal":[70],"projection":[71],"matrix":[72],"such":[76],"that":[77,81,114],"on":[80,106],"subspace":[82],"can":[83],"achieve":[84],"high":[86],"discrimination":[87],"classification.":[89],"Then,":[90],"projected":[92],"coefficients":[93],"are":[94],"executed":[95],"by":[96],"Extensive":[102],"experiments":[103],"carried":[104],"out":[105],"FERET":[108],"and":[109,125],"AR":[110],"databases":[112],"show":[113],"performs":[117],"better":[118],"than":[119],"related":[121],"based":[123],"algorithms":[124],"shows":[126],"promising":[128],"ability":[129]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":16},{"year":2015,"cited_by_count":8},{"year":2014,"cited_by_count":8},{"year":2013,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}