{"id":"https://openalex.org/W1991835793","doi":"https://doi.org/10.1117/1.2885164","title":"Confidence interval of feature number selection for face recognition","display_name":"Confidence interval of feature number selection for face recognition","publication_year":2008,"publication_date":"2008-01-01","ids":{"openalex":"https://openalex.org/W1991835793","doi":"https://doi.org/10.1117/1.2885164","mag":"1991835793"},"language":"en","primary_location":{"id":"doi:10.1117/1.2885164","is_oa":false,"landing_page_url":"https://doi.org/10.1117/1.2885164","pdf_url":null,"source":{"id":"https://openalex.org/S158511090","display_name":"Journal of Electronic Imaging","issn_l":"1017-9909","issn":["1017-9909","1560-229X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Electronic Imaging","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/A5054564234","display_name":"Yanjun Yan","orcid":"https://orcid.org/0000-0002-5152-6614"},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yanjun Yan","raw_affiliation_strings":["Syracuse Univ. (United States)","Syracuse University, Department of Electrical Engineering and Computer Science, Syracuse, New York 13224"],"affiliations":[{"raw_affiliation_string":"Syracuse Univ. (United States)","institution_ids":["https://openalex.org/I70983195"]},{"raw_affiliation_string":"Syracuse University, Department of Electrical Engineering and Computer Science, Syracuse, New York 13224","institution_ids":["https://openalex.org/I70983195"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5054564234"],"corresponding_institution_ids":["https://openalex.org/I70983195"],"apc_list":null,"apc_paid":null,"fwci":1.0535,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.78274872,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"17","issue":"1","first_page":"011002","last_page":"011002"},"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":0.9854000210762024,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9799000024795532,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7166721224784851},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.6530719995498657},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6497650742530823},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5714111328125},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5627864599227905},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5087361931800842},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5044792890548706},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.49557673931121826},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49194952845573425},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.4752518832683563},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.4168770909309387},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3274708390235901}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7166721224784851},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.6530719995498657},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6497650742530823},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5714111328125},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5627864599227905},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5087361931800842},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5044792890548706},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.49557673931121826},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49194952845573425},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.4752518832683563},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.4168770909309387},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3274708390235901},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","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/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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/1.2885164","is_oa":false,"landing_page_url":"https://doi.org/10.1117/1.2885164","pdf_url":null,"source":{"id":"https://openalex.org/S158511090","display_name":"Journal of Electronic Imaging","issn_l":"1017-9909","issn":["1017-9909","1560-229X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Electronic Imaging","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6000000238418579}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1968210270","https://openalex.org/W1972334750","https://openalex.org/W1983836944","https://openalex.org/W1985809919","https://openalex.org/W2013605417","https://openalex.org/W2033419168","https://openalex.org/W2034677010","https://openalex.org/W2056684807","https://openalex.org/W2071128523","https://openalex.org/W2088900896","https://openalex.org/W2105903591","https://openalex.org/W2108239416","https://openalex.org/W2112043903","https://openalex.org/W2116019577","https://openalex.org/W2121647436","https://openalex.org/W2130972944","https://openalex.org/W2132549764","https://openalex.org/W2134262590","https://openalex.org/W2136405083","https://openalex.org/W2138451337","https://openalex.org/W2150761159","https://openalex.org/W2158114849","https://openalex.org/W2165918462","https://openalex.org/W6676314883"],"related_works":["https://openalex.org/W1975632186","https://openalex.org/W3027745756","https://openalex.org/W3205213561","https://openalex.org/W2531880140","https://openalex.org/W2126145365","https://openalex.org/W2388958958","https://openalex.org/W4386564352","https://openalex.org/W2952668426","https://openalex.org/W2132337154","https://openalex.org/W2384651879"],"abstract_inverted_index":{"We":[0],"propose":[1,76],"a":[2,77],"multistep":[3],"statistical":[4],"procedure":[5],"to":[6,37,54,85,111,178],"determine":[7],"the":[8,12,28,40,60,64,87,91,97,105,117,125,152,155,172],"confidence":[9,88],"interval":[10,89],"of":[11,14,31,90,93,148,154],"number":[13,92,147],"features":[15,139,149],"that":[16,124,135],"should":[17],"be":[18,182],"retained":[19],"in":[20,100,184],"appearance-based":[21],"face":[22,101,167],"recognition,":[23,168],"which":[24,69],"is":[25,52,67,132,161],"based":[26,129],"on":[27,116,130],"eigen":[29],"decomposition":[30],"covariance":[32],"matrices.":[33],"In":[34],"practice,":[35],"due":[36],"sampling":[38],"variation,":[39],"empirical":[41,50],"eigenpairs":[42],"differ":[43],"from":[44,59,109,134,176],"their":[45],"underlying":[46],"population":[47],"counterparts.":[48],"The":[49,113,144],"distribution":[51],"difficult":[53],"derive,":[55],"and":[56,103,120,180],"it":[57,170],"deviates":[58],"asymptotic":[61],"approximation":[62],"when":[63],"sample":[65],"size":[66],"limited,":[68],"hinders":[70],"effective":[71],"feature":[72,157,164],"selection.":[73],"Hence,":[74],"we":[75],"new":[78],"technique,":[79],"MIZM":[80,95,131,160],"(modified":[81],"indifference":[82,106,173],"zone":[83,107,174],"method),":[84],"estimate":[86],"features.":[94,143],"overcomes":[96],"singularity":[98],"problem":[99],"recognition":[102,127],"extends":[104,171],"selection":[108,158,165],"PCA":[110,177],"LDA.":[112],"simulation":[114],"results":[115],"ORL,":[118],"UMIST,":[119],"FERET":[121],"databases":[122],"show":[123],"overall":[126],"performance":[128],"improved":[133],"using":[136],"all":[137],"available":[138],"or":[140],"heuristically":[141],"selected":[142],"relatively":[145],"small":[146],"also":[150],"indicates":[151],"efficiency":[153],"proposed":[156],"method.":[159],"motivated":[162],"by":[163],"for":[166],"but":[169],"method":[175],"LDA":[179,186],"can":[181],"applied":[183],"general":[185],"tasks.":[187]},"counts_by_year":[{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}