{"id":"https://openalex.org/W2026505325","doi":"https://doi.org/10.4018/ijcvip.2012040104","title":"Local Linear Regression on Hybrid Eigenfaces for Pose Invariant Face Recognition","display_name":"Local Linear Regression on Hybrid Eigenfaces for Pose Invariant Face Recognition","publication_year":2012,"publication_date":"2012-04-01","ids":{"openalex":"https://openalex.org/W2026505325","doi":"https://doi.org/10.4018/ijcvip.2012040104","mag":"2026505325"},"language":"en","primary_location":{"id":"doi:10.4018/ijcvip.2012040104","is_oa":false,"landing_page_url":"https://doi.org/10.4018/ijcvip.2012040104","pdf_url":null,"source":{"id":"https://openalex.org/S4210177549","display_name":"International Journal of Computer Vision and Image Processing","issn_l":"2155-6989","issn":["2155-6989","2155-6997"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Vision and Image Processing","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/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, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jawaharlal Nehru University, India","institution_ids":["https://openalex.org/I152429107"]}]},{"author_position":"middle","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, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jawaharlal Nehru University, 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, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jawaharlal Nehru University, 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":0.56987861,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"2","issue":"2","first_page":"48","last_page":"58"},"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":0.9991999864578247,"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":0.9894000291824341,"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/eigenface","display_name":"Eigenface","score":0.976884126663208},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.6831990480422974},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6691176295280457},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6186321973800659},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6034830212593079},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5107789039611816},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4966197609901428},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.4941575825214386},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4721662700176239},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.46008870005607605},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21198788285255432},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13524267077445984}],"concepts":[{"id":"https://openalex.org/C104906051","wikidata":"https://www.wikidata.org/wiki/Q29695","display_name":"Eigenface","level":4,"score":0.976884126663208},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.6831990480422974},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6691176295280457},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6186321973800659},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6034830212593079},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5107789039611816},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4966197609901428},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.4941575825214386},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4721662700176239},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.46008870005607605},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21198788285255432},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13524267077445984},{"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/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.4018/ijcvip.2012040104","is_oa":false,"landing_page_url":"https://doi.org/10.4018/ijcvip.2012040104","pdf_url":null,"source":{"id":"https://openalex.org/S4210177549","display_name":"International Journal of Computer Vision and Image Processing","issn_l":"2155-6989","issn":["2155-6989","2155-6997"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computer Vision and Image Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1989702938","https://openalex.org/W1997011019","https://openalex.org/W2006793117","https://openalex.org/W2010209470","https://openalex.org/W2018268072","https://openalex.org/W2026439792","https://openalex.org/W2029835507","https://openalex.org/W2044270390","https://openalex.org/W2044701250","https://openalex.org/W2049494507","https://openalex.org/W2073644493","https://openalex.org/W2078118580","https://openalex.org/W2095999100","https://openalex.org/W2097437748","https://openalex.org/W2098693229","https://openalex.org/W2098947662","https://openalex.org/W2101055828","https://openalex.org/W2108767394","https://openalex.org/W2117820831","https://openalex.org/W2120954940","https://openalex.org/W2121647436","https://openalex.org/W2123921160","https://openalex.org/W2128178088","https://openalex.org/W2130093472","https://openalex.org/W2131518659","https://openalex.org/W2137695006","https://openalex.org/W2140095548","https://openalex.org/W2147575376","https://openalex.org/W2148100798","https://openalex.org/W2148763637","https://openalex.org/W2152340032","https://openalex.org/W2152826865","https://openalex.org/W2157637043","https://openalex.org/W2160126058","https://openalex.org/W2160254522","https://openalex.org/W2163808566","https://openalex.org/W2164071167","https://openalex.org/W2166125343","https://openalex.org/W2166743687","https://openalex.org/W2170960656","https://openalex.org/W2171937595","https://openalex.org/W2180187800","https://openalex.org/W3126588943"],"related_works":["https://openalex.org/W3160911891","https://openalex.org/W2779406006","https://openalex.org/W2292842372","https://openalex.org/W2797230162","https://openalex.org/W2000101267","https://openalex.org/W2391937622","https://openalex.org/W4364362336","https://openalex.org/W2086208164","https://openalex.org/W2340256886","https://openalex.org/W1994017132"],"abstract_inverted_index":{"Pose":[0],"variation":[1],"leads":[2],"to":[3,34,48,100],"significant":[4],"decline":[5],"in":[6,55],"the":[7,10,17,69,93,117,120,132],"performance":[8,67],"of":[9,27,68,95,97,119,125,134],"face":[11,36,114],"recognition":[12,37],"systems.":[13],"In":[14,40],"this":[15,41],"paper,":[16],"authors":[18],"propose":[19],"a":[20],"new":[21],"approach":[22,71,127],"HLLR,":[23],"based":[24,81],"on":[25,44,82,86,103,108],"conjunction":[26],"hybrid-eigenfaces":[28,45,102],"and":[29,57],"local":[30],"linear":[31,84],"regression":[32,85],"(LLR),":[33],"perform":[35],"across":[38],"pose.":[39],"approach,":[42],"LLR":[43],"is":[46,72,128,137],"used":[47,99],"generate":[49],"virtual":[50,53],"views.":[51],"These":[52],"views":[54],"frontal":[56,63],"non-frontal":[58],"poses":[59],"are":[60],"obtained":[61],"using":[62],"gallery":[64],"image.":[65],"The":[66,123],"proposed":[70,121,126],"compared":[73],"for":[74],"classification":[75,104],"accuracy":[76],"with":[77],"another":[78],"efficient":[79],"method":[80],"global":[83],"hybrid":[87],"eigenface":[88],"(HGLR).":[89],"They":[90],"also":[91,129],"investigate":[92],"effect":[94],"number":[96,133],"images":[98,136],"construct":[101],"accuracy.":[105],"Experimental":[106],"results":[107],"two":[109],"well":[110],"known":[111],"publicly":[112],"available":[113,135],"databases":[115],"demonstrate":[116],"effectiveness":[118],"approach.":[122],"suitability":[124],"noticed":[130],"when":[131],"small.":[138]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}