{"id":"https://openalex.org/W2072481464","doi":"https://doi.org/10.1109/ijcnn.2014.6889754","title":"Facial expressions recognition system using Bayesian inference","display_name":"Facial expressions recognition system using Bayesian inference","publication_year":2014,"publication_date":"2014-07-01","ids":{"openalex":"https://openalex.org/W2072481464","doi":"https://doi.org/10.1109/ijcnn.2014.6889754","mag":"2072481464"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2014.6889754","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2014.6889754","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Joint Conference on Neural Networks (IJCNN)","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/A5046155808","display_name":"Maninderjit Singh","orcid":null},"institutions":[{"id":"https://openalex.org/I94234084","display_name":"Indian Institute of Technology Kanpur","ror":"https://ror.org/05pjsgx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I94234084"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Maninderjit Singh","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology, Kanpur, Uttar Pradesh, India","Department of Electrical Engineering, Indian Institute of Technology Kanpur, PIN 208016, Uttar Pradesh, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology, Kanpur, Uttar Pradesh, India","institution_ids":["https://openalex.org/I94234084"]},{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Kanpur, PIN 208016, Uttar Pradesh, India","institution_ids":["https://openalex.org/I94234084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009996322","display_name":"Anima Majumder","orcid":"https://orcid.org/0000-0002-6300-010X"},"institutions":[{"id":"https://openalex.org/I94234084","display_name":"Indian Institute of Technology Kanpur","ror":"https://ror.org/05pjsgx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I94234084"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Anima Majumder","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology, Kanpur, Uttar Pradesh, India","Department of Electrical Engineering, Indian Institute of Technology Kanpur, PIN 208016, Uttar Pradesh, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology, Kanpur, Uttar Pradesh, India","institution_ids":["https://openalex.org/I94234084"]},{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Kanpur, PIN 208016, Uttar Pradesh, India","institution_ids":["https://openalex.org/I94234084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065056581","display_name":"Laxmidhar Behera","orcid":"https://orcid.org/0000-0003-1879-5609"},"institutions":[{"id":"https://openalex.org/I94234084","display_name":"Indian Institute of Technology Kanpur","ror":"https://ror.org/05pjsgx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I94234084"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Laxmidhar Behera","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology, Kanpur, Uttar Pradesh, India","Department of Electrical Engineering, Indian Institute of Technology Kanpur, PIN 208016, Uttar Pradesh, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology, Kanpur, Uttar Pradesh, India","institution_ids":["https://openalex.org/I94234084"]},{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Kanpur, PIN 208016, Uttar Pradesh, India","institution_ids":["https://openalex.org/I94234084"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5046155808"],"corresponding_institution_ids":["https://openalex.org/I94234084"],"apc_list":null,"apc_paid":null,"fwci":0.72342463,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.76861009,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1502","last_page":"1509"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9988999962806702,"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":0.9988999962806702,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9853000044822693,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7390830516815186},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6374104022979736},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5433401465415955},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5084666013717651},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.49616774916648865},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.43561404943466187},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33447352051734924}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7390830516815186},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6374104022979736},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5433401465415955},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5084666013717651},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.49616774916648865},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.43561404943466187},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33447352051734924}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2014.6889754","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2014.6889754","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6399999856948853,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1535430927","https://openalex.org/W1588539311","https://openalex.org/W1968985103","https://openalex.org/W2036250785","https://openalex.org/W2044188769","https://openalex.org/W2103943262","https://openalex.org/W2104680354","https://openalex.org/W2108445559","https://openalex.org/W2112393832","https://openalex.org/W2120885766","https://openalex.org/W2133180260","https://openalex.org/W2133990480","https://openalex.org/W2139900086","https://openalex.org/W2139916508","https://openalex.org/W2145867514","https://openalex.org/W2165183780","https://openalex.org/W2172279486","https://openalex.org/W2249628608","https://openalex.org/W4242680962","https://openalex.org/W6681551814"],"related_works":["https://openalex.org/W2372267530","https://openalex.org/W2969189870","https://openalex.org/W4303857162","https://openalex.org/W2965643117","https://openalex.org/W2407375987","https://openalex.org/W2505726097","https://openalex.org/W2950975704","https://openalex.org/W2010643158","https://openalex.org/W3049691116","https://openalex.org/W2106867672"],"abstract_inverted_index":{"The":[0,74,85,229,245],"paper":[1],"presents":[2],"a":[3,149],"facial":[4,22,58,82,98,128,134],"expressions":[5],"recognition":[6,186],"system":[7,137],"using":[8,15,151,192],"Bayesian":[9,194,235],"network.":[10,228],"We":[11,32,146],"train":[12],"the":[13,61,81,140,157,206,209,234,249,252],"network":[14,195,236],"probabilistic":[16],"modeling":[17],"that":[18,102,164,233],"draws":[19,165],"relationship":[20,166],"between":[21],"features,":[23],"action":[24,135],"units":[25],"and":[26,45,139,169,224],"finally":[27],"recognizes":[28],"six":[29],"basic":[30],"emotions.":[31],"propose":[33,148],"features":[34,87],"extraction":[35,88],"methods":[36],"to":[37,67,154],"get":[38],"geometric":[39,86],"feature":[40,47,62,106,202],"vector":[41,48,220],"containing":[42,49],"angular":[43,75,94,123,201],"informations":[44,76,95],"appearance":[46],"moments":[50],"extracted":[51,79],"after":[52],"applying":[53],"gabor":[54],"filter":[55],"over":[56],"certain":[57],"regions.":[59],"Both":[60],"vectors":[63],"are":[64,77,110,131],"further":[65],"used":[66,178],"draw":[68],"relationships":[69],"among":[70,167],"Action":[71],"Units":[72],"(AUs).":[73],"directly":[78],"from":[80],"landmark":[83,119],"points.":[84],"approach":[89,101,197,211,239],"contains":[90,103,118],"only":[91],"22":[92,199],"dimensional":[93,105,200],"against":[96],"direct":[97],"landmarks":[99],"based":[100,196,237],"136":[104],"vector.":[107,203],"Facial":[108],"activities":[109],"represented":[111],"by":[112],"three":[113,214],"distinct":[114],"layers.":[115],"Bottom":[116],"level":[117,126],"measurement":[120,170],"data":[121],"with":[122],"features.":[124],"Middle":[125],"has":[127],"AUs":[129,168],"those":[130],"coded":[132],"in":[133,161],"coding":[136],"(FACS)":[138],"top":[141],"level,":[142],"represents":[143],"emotion":[144,185],"node.":[145],"also":[147],"method":[150],"k-means":[152],"clustering":[153],"automatically":[155],"define":[156],"states":[158],"of":[159,188,208,251],"nodes":[160],"anatomical":[162],"layer":[163],"data.":[171],"Extended":[172],"Cohn":[173],"Kanade":[174],"Database":[175],"is":[176,190],"being":[177],"for":[179,198],"our":[180],"experimental":[181,246],"purposes.":[182],"An":[183],"average":[184],"accuracy":[187],"95.7%":[189],"achieved":[191],"proposed":[193,210,253],"To":[204],"verify":[205],"performance":[207],"we":[212],"apply":[213],"different":[215],"classifiers":[216],"such":[217],"as,":[218],"Support":[219],"machine,":[221],"Decision":[222],"tree":[223],"Radial":[225],"basis":[226],"functions":[227],"confusion":[230],"matrices":[231],"show":[232],"classification":[238],"outperforms":[240],"all":[241],"other":[242],"applied":[243],"approaches.":[244],"results":[247],"illustrates":[248],"effectiveness":[250],"model.":[254]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
