{"id":"https://openalex.org/W1973827079","doi":"https://doi.org/10.1145/2345396.2345547","title":"Performance evaluation of subspace methods to tackle small sample size problem in face recognition","display_name":"Performance evaluation of subspace methods to tackle small sample size problem in face recognition","publication_year":2012,"publication_date":"2012-08-03","ids":{"openalex":"https://openalex.org/W1973827079","doi":"https://doi.org/10.1145/2345396.2345547","mag":"1973827079"},"language":"en","primary_location":{"id":"doi:10.1145/2345396.2345547","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2345396.2345547","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Advances in Computing, Communications and Informatics","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/A5047086595","display_name":"Nitin Kumar","orcid":"https://orcid.org/0000-0003-4242-6125"},"institutions":[{"id":"https://openalex.org/I152429107","display_name":"Jawaharlal Nehru University","ror":"https://ror.org/0567v8t28","country_code":"IN","type":"education","lineage":["https://openalex.org/I152429107"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Nitin Kumar","raw_affiliation_strings":["Jawaharlal Nehru University, New Delhi - India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jawaharlal Nehru University, New Delhi - India","institution_ids":["https://openalex.org/I152429107"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034136464","display_name":"Ajay Jaiswal","orcid":"https://orcid.org/0000-0001-9032-2916"},"institutions":[{"id":"https://openalex.org/I152429107","display_name":"Jawaharlal Nehru University","ror":"https://ror.org/0567v8t28","country_code":"IN","type":"education","lineage":["https://openalex.org/I152429107"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ajay Jaiswal","raw_affiliation_strings":["Jawaharlal Nehru University, New Delhi - India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jawaharlal Nehru University, New Delhi - India","institution_ids":["https://openalex.org/I152429107"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103154659","display_name":"R. K. Agrawal","orcid":"https://orcid.org/0000-0003-3122-5096"},"institutions":[{"id":"https://openalex.org/I152429107","display_name":"Jawaharlal Nehru University","ror":"https://ror.org/0567v8t28","country_code":"IN","type":"education","lineage":["https://openalex.org/I152429107"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"R. K. Agrawal","raw_affiliation_strings":["Jawaharlal Nehru University, New Delhi - India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jawaharlal Nehru University, New Delhi - India","institution_ids":["https://openalex.org/I152429107"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2776,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.54573945,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"938","last_page":"944"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9081000089645386,"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":0.8500009775161743},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.8424620628356934},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.8101561069488525},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7419583797454834},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.679481565952301},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.6644218564033508},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.618500292301178},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5650836229324341},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5138364434242249},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.49612554907798767},{"id":"https://openalex.org/keywords/random-subspace-method","display_name":"Random subspace method","score":0.46260201930999756},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.43934327363967896},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3222276568412781}],"concepts":[{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.8500009775161743},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.8424620628356934},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.8101561069488525},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7419583797454834},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.679481565952301},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.6644218564033508},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.618500292301178},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5650836229324341},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5138364434242249},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.49612554907798767},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.46260201930999756},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.43934327363967896},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3222276568412781},{"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/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2345396.2345547","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2345396.2345547","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Advances in Computing, Communications and Informatics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6899999976158142,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1570904403","https://openalex.org/W1591385104","https://openalex.org/W1598196523","https://openalex.org/W1989702938","https://openalex.org/W2024534252","https://openalex.org/W2065520107","https://openalex.org/W2078099122","https://openalex.org/W2088900896","https://openalex.org/W2095999100","https://openalex.org/W2121647436","https://openalex.org/W2123180320","https://openalex.org/W2123921160","https://openalex.org/W2125874614","https://openalex.org/W2134262590","https://openalex.org/W2138451337","https://openalex.org/W2144143728","https://openalex.org/W2154691736","https://openalex.org/W2160126058","https://openalex.org/W2167711430","https://openalex.org/W2171347282"],"related_works":["https://openalex.org/W2350751952","https://openalex.org/W1999647744","https://openalex.org/W2362114017","https://openalex.org/W3147024994","https://openalex.org/W2063246903","https://openalex.org/W2374055396","https://openalex.org/W1978302214","https://openalex.org/W2021817983","https://openalex.org/W1995039490","https://openalex.org/W3008559849"],"abstract_inverted_index":{"Linear":[0],"Discriminant":[1,86],"Analysis":[2,87],"(LDA)":[3],"has":[4],"been":[5,35,94],"one":[6],"of":[7,30,65,115,132,140,157,168],"the":[8,20,51,63,123,127,130,141,149,155,169,175],"popular":[9,67],"subspace":[10,68,150],"methods":[11,69,151],"for":[12],"face":[13,100,179],"recognition.":[14,180],"But":[15,43],"this":[16,41,58],"method":[17,49],"suffers":[18],"from":[19],"small":[21],"sample":[22],"size":[23],"(SSS)":[24],"problem,":[25],"also":[26,173],"known":[27],"as":[28,71],"'curse":[29],"dimensionality'.":[31],"Various":[32],"techniques":[33],"have":[34,61,93],"proposed":[36],"in":[37,113,129,136,163,178],"literature":[38],"to":[39,54],"overcome":[40],"limitation.":[42],"it":[44],"is":[45,111,144,161],"still":[46],"unclear":[47],"which":[48],"provides":[50],"best":[52],"solution":[53],"SSS":[55,165],"problem.":[56],"In":[57],"paper,":[59],"we":[60],"investigated":[62],"performance":[64,110,124,156],"some":[66],"such":[70],"principal":[72],"component":[73],"analysis":[74],"(PCA),":[75],"PCA":[76],"+":[77],"LDA,":[78,84],"LDA":[79],"via":[80],"QR":[81],"decomposition,":[82],"Null-space":[83],"Exponential":[85],"(EDA),":[88],"PCA+EDA":[89,160],"etc.":[90],"Extensive":[91],"experiments":[92],"performed":[95],"on":[96],"five":[97],"publically":[98],"available":[99],"datasets":[101],"viz.":[102],"AR,":[103],"CMU-PIE,":[104],"PIX,":[105],"Yale":[106],"and":[107,159,171],"YaleB.":[108],"The":[109],"measured":[112],"terms":[114],"average":[116],"classification":[117],"accuracy.":[118],"Experimental":[119],"results":[120],"show":[121],"that":[122],"increases":[125],"with":[126],"increase":[128],"number":[131],"images":[133],"per":[134],"person":[135],"training":[137],"set":[138],"irrespective":[139,167],"datasets.":[142],"There":[143],"no":[145],"clear":[146],"winner":[147],"among":[148],"under":[152],"investigation.":[153],"But,":[154],"PCA+LDA":[158],"consistent":[162],"tackling":[164],"problem":[166],"dataset":[170],"can":[172],"handle":[174],"illumination":[176],"variation":[177]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
