{"id":"https://openalex.org/W2135623468","doi":"https://doi.org/10.1109/icme.2002.1035530","title":"Embedded Bayesian networks for face recognition","display_name":"Embedded Bayesian networks for face recognition","publication_year":2003,"publication_date":"2003-06-25","ids":{"openalex":"https://openalex.org/W2135623468","doi":"https://doi.org/10.1109/icme.2002.1035530","mag":"2135623468"},"language":"en","primary_location":{"id":"doi:10.1109/icme.2002.1035530","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2002.1035530","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. IEEE International Conference on Multimedia and Expo","raw_type":"proceedings-article"},"type":"conference-paper","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/A5113481101","display_name":"Ara Nefian","orcid":null},"institutions":[{"id":"https://openalex.org/I1343180700","display_name":"Intel (United States)","ror":"https://ror.org/01ek73717","country_code":"US","type":"company","lineage":["https://openalex.org/I1343180700"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"A.V. Nefian","raw_affiliation_strings":["Microprocessor Research Labs, Intel Corporation, Santa Clara, CA, USA","[Microprocessor Research Laboratories, Intel Corporation, Santa Clara, CA, USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microprocessor Research Labs, Intel Corporation, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I1343180700"]},{"raw_affiliation_string":"[Microprocessor Research Laboratories, Intel Corporation, Santa Clara, CA, USA]","institution_ids":["https://openalex.org/I1343180700"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5113481101"],"corresponding_institution_ids":["https://openalex.org/I1343180700"],"apc_list":null,"apc_paid":null,"fwci":3.7606,"has_fulltext":false,"cited_by_count":68,"citation_normalized_percentile":{"value":0.94272108,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"2","issue":null,"first_page":"133","last_page":"136"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.996399998664856,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/eigenface","display_name":"Eigenface","score":0.7883474826812744},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.7176687717437744},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7150720357894897},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6535612344741821},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.642678439617157},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.595217764377594},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5847086906433105},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5562489032745361},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5480114221572876},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.5291894674301147},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.507796585559845},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4534880518913269},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.42584025859832764},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4104993939399719},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39064133167266846},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1357954740524292},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06506362557411194}],"concepts":[{"id":"https://openalex.org/C104906051","wikidata":"https://www.wikidata.org/wiki/Q29695","display_name":"Eigenface","level":4,"score":0.7883474826812744},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.7176687717437744},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7150720357894897},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6535612344741821},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.642678439617157},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.595217764377594},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5847086906433105},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5562489032745361},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5480114221572876},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.5291894674301147},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.507796585559845},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4534880518913269},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.42584025859832764},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4104993939399719},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39064133167266846},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1357954740524292},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06506362557411194},{"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icme.2002.1035530","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2002.1035530","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. IEEE International Conference on Multimedia and Expo","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.501.4202","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.501.4202","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.anefian.com/research/nefian02_embedded.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.41999998688697815,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1480865305","https://openalex.org/W1560013842","https://openalex.org/W1833616679","https://openalex.org/W2024581784","https://openalex.org/W2098693229","https://openalex.org/W2098947662","https://openalex.org/W2099312605","https://openalex.org/W2102897151","https://openalex.org/W2113341759","https://openalex.org/W2115689562","https://openalex.org/W2121647436","https://openalex.org/W2136126387","https://openalex.org/W2144354855","https://openalex.org/W2152239535","https://openalex.org/W2156165250","https://openalex.org/W2164450870"],"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":{"The":[0],"embedded":[1,14,108],"Bayesian":[2,40],"networks":[3],"(EBN)":[4],"introduced":[5],"in":[6],"this":[7,84,101],"paper,":[8],"are":[9],"a":[10,31,39],"generalization":[11],"of":[12,55,71,90,100],"the":[13,35,45,48,53,56,69,91,98,104,107],"hidden":[15],"Markov":[16],"models":[17],"previously":[18],"used":[19],"for":[20,93],"face":[21,94],"and":[22,79,96,106],"character":[23],"recognition.":[24],"An":[25],"EBN":[26],"is":[27,38],"defined":[28],"recursively":[29],"as":[30],"hierarchical":[32],"structure":[33],"where":[34],"\"parent\"":[36],"node":[37],"network":[41],"(BN)":[42],"that":[43,51],"conditions":[44],"EBNs":[46,92],"or":[47],"observation":[49],"sequence":[50],"describes":[52],"nodes":[54],"\"child\"":[57],"layer.":[58],"With":[59],"an":[60,88],"EBN,":[61],"one":[62],"can":[63],"model":[64],"complex":[65],"N-dimensional":[66,72],"data,":[67],"avoiding":[68],"complexity":[70],"BNs":[73],"while":[74],"still":[75],"preserving":[76],"their":[77],"flexibility":[78],"partial":[80],"scale":[81],"invariance.":[82],"In":[83],"paper":[85],"we":[86],"present":[87],"application":[89],"recognition":[95],"show":[97],"improvement":[99],"approach":[102],"versus":[103],"\"eigenface\"":[105],"HMM":[109],"approaches.":[110]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":5},{"year":2012,"cited_by_count":8}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
