{"id":"https://openalex.org/W2097937070","doi":"https://doi.org/10.1109/fg.2013.6553755","title":"Ensemble of Randomized Linear Discriminant Analysis for face recognition with single sample per person","display_name":"Ensemble of Randomized Linear Discriminant Analysis for face recognition with single sample per person","publication_year":2013,"publication_date":"2013-04-01","ids":{"openalex":"https://openalex.org/W2097937070","doi":"https://doi.org/10.1109/fg.2013.6553755","mag":"2097937070"},"language":"en","primary_location":{"id":"doi:10.1109/fg.2013.6553755","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg.2013.6553755","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)","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/A5100785617","display_name":"Ying Li","orcid":"https://orcid.org/0000-0001-7370-1754"},"institutions":[{"id":"https://openalex.org/I192455969","display_name":"York University","ror":"https://ror.org/05fq50484","country_code":"CA","type":"education","lineage":["https://openalex.org/I192455969"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Ying Li","raw_affiliation_strings":["Electrical Engineering, Mathematics and Computer Science, York university, Toronto, ONT, Canada","Electr. Eng., Math. & Comput. Sci., York Univ., Toronto, ON, Canada"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering, Mathematics and Computer Science, York university, Toronto, ONT, Canada","institution_ids":["https://openalex.org/I192455969"]},{"raw_affiliation_string":"Electr. Eng., Math. & Comput. Sci., York Univ., Toronto, ON, Canada","institution_ids":["https://openalex.org/I192455969"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048353325","display_name":"Wei Shen","orcid":"https://orcid.org/0000-0002-1235-598X"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Shen","raw_affiliation_strings":["Faculty of Department of Communication Engineering, Shanghai University, Shanghai, China","Fac. of Dept. of Commun. Eng., Shanghai Univ., Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Department of Communication Engineering, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]},{"raw_affiliation_string":"Fac. of Dept. of Commun. Eng., Shanghai Univ., Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102227809","display_name":"Xun Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210108701","display_name":"Magnum Semiconductor (Canada)","ror":"https://ror.org/0159eq874","country_code":"CA","type":"company","lineage":["https://openalex.org/I4210108701"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Xun Shi","raw_affiliation_strings":["Magnum Semiconductor, Inc., Waterloo, ONT, Canada","Magnum Semicond., Waterloo, ON, Canada"],"affiliations":[{"raw_affiliation_string":"Magnum Semiconductor, Inc., Waterloo, ONT, Canada","institution_ids":["https://openalex.org/I4210108701"]},{"raw_affiliation_string":"Magnum Semicond., Waterloo, ON, Canada","institution_ids":["https://openalex.org/I4210108701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100696203","display_name":"Zhijiang Zhang","orcid":"https://orcid.org/0000-0002-7699-0747"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhijiang Zhang","raw_affiliation_strings":["Faculty of Department of Communication Engineering, Shanghai University, Shanghai, China","Fac. of Dept. of Commun. Eng., Shanghai Univ., Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Faculty of Department of Communication Engineering, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]},{"raw_affiliation_string":"Fac. of Dept. of Commun. Eng., Shanghai Univ., Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100785617"],"corresponding_institution_ids":["https://openalex.org/I192455969"],"apc_list":null,"apc_paid":null,"fwci":1.3826,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.84578422,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9990000128746033,"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":0.9883999824523926,"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/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.8186006546020508},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7496331930160522},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6904871463775635},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.6835818290710449},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6550734043121338},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5373429656028748},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5233539938926697},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5057334899902344},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4981856346130371},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.49741366505622864},{"id":"https://openalex.org/keywords/kernel-fisher-discriminant-analysis","display_name":"Kernel Fisher discriminant analysis","score":0.4797267019748688},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.4793337285518646},{"id":"https://openalex.org/keywords/linear-subspace","display_name":"Linear subspace","score":0.4762989580631256},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.427426815032959},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22102689743041992}],"concepts":[{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.8186006546020508},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7496331930160522},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6904871463775635},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.6835818290710449},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6550734043121338},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5373429656028748},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5233539938926697},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5057334899902344},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4981856346130371},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.49741366505622864},{"id":"https://openalex.org/C181367576","wikidata":"https://www.wikidata.org/wiki/Q6394184","display_name":"Kernel Fisher discriminant analysis","level":4,"score":0.4797267019748688},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4793337285518646},{"id":"https://openalex.org/C12362212","wikidata":"https://www.wikidata.org/wiki/Q728435","display_name":"Linear subspace","level":2,"score":0.4762989580631256},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.427426815032959},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22102689743041992},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/fg.2013.6553755","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg.2013.6553755","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.716.5915","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.716.5915","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://wei-shen.weebly.com/uploads/2/3/8/2/23825939/ensemble_of_randomized_linear_discriminant_analysis_for_face_recognition_with_single_sample_per_person.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7400000095367432,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1486890033","https://openalex.org/W1782590233","https://openalex.org/W1989702938","https://openalex.org/W1991158974","https://openalex.org/W2001947174","https://openalex.org/W2033419168","https://openalex.org/W2038165640","https://openalex.org/W2061255502","https://openalex.org/W2062019416","https://openalex.org/W2070343473","https://openalex.org/W2083965952","https://openalex.org/W2092131162","https://openalex.org/W2095189186","https://openalex.org/W2102544846","https://openalex.org/W2103560185","https://openalex.org/W2107179775","https://openalex.org/W2108767394","https://openalex.org/W2121647436","https://openalex.org/W2138451337","https://openalex.org/W2140095548","https://openalex.org/W2155190225","https://openalex.org/W2165052637","https://openalex.org/W2169635990","https://openalex.org/W2184186989","https://openalex.org/W2184217733","https://openalex.org/W3097096317","https://openalex.org/W4236803189","https://openalex.org/W4285719527","https://openalex.org/W6629217351","https://openalex.org/W6648329832","https://openalex.org/W6673347455","https://openalex.org/W6676220612","https://openalex.org/W6682790200","https://openalex.org/W6686497387"],"related_works":["https://openalex.org/W1978302214","https://openalex.org/W3147024994","https://openalex.org/W2162393942","https://openalex.org/W2321869780","https://openalex.org/W2025089370","https://openalex.org/W1984472287","https://openalex.org/W2371177901","https://openalex.org/W2589829774","https://openalex.org/W1570195136","https://openalex.org/W2021817983"],"abstract_inverted_index":{"Linear":[0],"Discriminant":[1],"Analysis":[2],"(LDA)":[3],"has":[4],"been":[5],"widely":[6],"used":[7],"in":[8,37,58],"appearance-based":[9],"face":[10,139],"recognition.":[11,140],"However,":[12],"it":[13],"requires":[14],"lots":[15],"of":[16,28,44,90,111,127,138],"training":[17,45,52,106],"samples":[18,107],"for":[19,66],"each":[20],"person":[21,55],"with":[22,77],"respect":[23],"to":[24,35,102,117],"the":[25,29,41,59,94,125,128,133],"large":[26],"dimensionality":[27],"image":[30,80],"space,":[31],"which":[32],"is":[33,120],"difficult":[34],"collect":[36],"reality.":[38],"To":[39],"overcome":[40],"severe":[42],"constraint":[43],"sample":[46,53],"deficiency,":[47],"approaches":[48],"based":[49],"on":[50,108,135],"single":[51],"per":[54],"(SSPP)":[56],"arise":[57],"past":[60],"decades.":[61],"Though":[62],"making":[63],"great":[64],"improvements":[65],"years,":[67],"these":[68],"methods":[69,130],"still":[70],"suffer":[71],"from":[72],"low":[73],"accuracy":[74],"when":[75],"dealing":[76],"high":[78],"dimensional":[79],"features.":[81],"In":[82],"this":[83],"paper,":[84],"we":[85],"develop":[86],"a":[87],"new":[88],"variant":[89],"LDA":[91],"that":[92,131],"addresses":[93],"SSPP":[95],"problem":[96],"especially":[97],"and":[98],"apply":[99],"random":[100],"projections":[101],"generate":[103],"extra":[104],"useful":[105],"an":[109],"ensemble":[110],"low-dimensional":[112],"subspaces.":[113],"A":[114],"novel":[115],"extension":[116],"kernel":[118],"version":[119],"also":[121],"presented.":[122],"We":[123],"demonstrate":[124],"functionality":[126],"proposed":[129],"outperform":[132],"state-of-the-arts":[134],"several":[136],"benchmarks":[137]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":3}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}