{"id":"https://openalex.org/W2023084425","doi":"https://doi.org/10.1109/icmew.2013.6618337","title":"Latent Facial Topics for affect analysis","display_name":"Latent Facial Topics for affect analysis","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W2023084425","doi":"https://doi.org/10.1109/icmew.2013.6618337","mag":"2023084425"},"language":"en","primary_location":{"id":"doi:10.1109/icmew.2013.6618337","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew.2013.6618337","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)","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/A5054594732","display_name":"Prasanth Lade","orcid":null},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Prasanth Lade","raw_affiliation_strings":["Center for Cognitive Ubiquitous Computing, Arizona State University, USA","Center for Cognitive Ubiquitous Comput., Arizona State Univ., Tempe, AZ, USA"],"affiliations":[{"raw_affiliation_string":"Center for Cognitive Ubiquitous Computing, Arizona State University, USA","institution_ids":["https://openalex.org/I55732556"]},{"raw_affiliation_string":"Center for Cognitive Ubiquitous Comput., Arizona State Univ., Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038020125","display_name":"Vineeth N Balasubramanian","orcid":"https://orcid.org/0000-0003-2656-0375"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vineeth N Balasubramanian","raw_affiliation_strings":["Center for Cognitive Ubiquitous Computing, Arizona State University, USA","Center for Cognitive Ubiquitous Comput., Arizona State Univ., Tempe, AZ, USA"],"affiliations":[{"raw_affiliation_string":"Center for Cognitive Ubiquitous Computing, Arizona State University, USA","institution_ids":["https://openalex.org/I55732556"]},{"raw_affiliation_string":"Center for Cognitive Ubiquitous Comput., Arizona State Univ., Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066190233","display_name":"Sethuraman Panchanathan","orcid":"https://orcid.org/0000-0002-8769-6340"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sethuraman Panchanathan","raw_affiliation_strings":["Center for Cognitive Ubiquitous Computing, Arizona State University, USA","Center for Cognitive Ubiquitous Comput., Arizona State Univ., Tempe, AZ, USA"],"affiliations":[{"raw_affiliation_string":"Center for Cognitive Ubiquitous Computing, Arizona State University, USA","institution_ids":["https://openalex.org/I55732556"]},{"raw_affiliation_string":"Center for Cognitive Ubiquitous Comput., Arizona State Univ., Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5054594732"],"corresponding_institution_ids":["https://openalex.org/I55732556"],"apc_list":null,"apc_paid":null,"fwci":0.6301,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.75151001,"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":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9998000264167786,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9919000267982483,"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"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9822999835014343,"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/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.9035102128982544},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6687608957290649},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.6444433927536011},{"id":"https://openalex.org/keywords/affect","display_name":"Affect (linguistics)","score":0.5819732546806335},{"id":"https://openalex.org/keywords/valence","display_name":"Valence (chemistry)","score":0.535874605178833},{"id":"https://openalex.org/keywords/affective-computing","display_name":"Affective computing","score":0.5267322063446045},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.5052042603492737},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.49834418296813965},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4722014367580414},{"id":"https://openalex.org/keywords/arousal","display_name":"Arousal","score":0.46079379320144653},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4461299180984497},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4311942458152771},{"id":"https://openalex.org/keywords/latent-semantic-analysis","display_name":"Latent semantic analysis","score":0.42429083585739136},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.41135331988334656},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.3952937722206116},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36474552750587463},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3437075614929199},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3381422162055969},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33192646503448486},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.17614495754241943},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.09952950477600098},{"id":"https://openalex.org/keywords/communication","display_name":"Communication","score":0.08020219206809998}],"concepts":[{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.9035102128982544},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6687608957290649},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.6444433927536011},{"id":"https://openalex.org/C2776035688","wikidata":"https://www.wikidata.org/wiki/Q1606558","display_name":"Affect (linguistics)","level":2,"score":0.5819732546806335},{"id":"https://openalex.org/C168900304","wikidata":"https://www.wikidata.org/wiki/Q171407","display_name":"Valence (chemistry)","level":2,"score":0.535874605178833},{"id":"https://openalex.org/C6438553","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Affective computing","level":2,"score":0.5267322063446045},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.5052042603492737},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.49834418296813965},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4722014367580414},{"id":"https://openalex.org/C36951298","wikidata":"https://www.wikidata.org/wiki/Q379784","display_name":"Arousal","level":2,"score":0.46079379320144653},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4461299180984497},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4311942458152771},{"id":"https://openalex.org/C170133592","wikidata":"https://www.wikidata.org/wiki/Q1806883","display_name":"Latent semantic analysis","level":2,"score":0.42429083585739136},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.41135331988334656},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.3952937722206116},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36474552750587463},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3437075614929199},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3381422162055969},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33192646503448486},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.17614495754241943},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.09952950477600098},{"id":"https://openalex.org/C46312422","wikidata":"https://www.wikidata.org/wiki/Q11024","display_name":"Communication","level":1,"score":0.08020219206809998},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icmew.2013.6618337","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew.2013.6618337","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)","raw_type":"proceedings-article"},{"id":"pmh:oai:raiith.iith.ac.in:6132","is_oa":false,"landing_page_url":"http://raiith.iith.ac.in/6132/","pdf_url":null,"source":{"id":"https://openalex.org/S4306400292","display_name":"Research Archive of Indian Institute of Technology Hyderabad (Indian Institute of Technology Hyderabad)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I65181880","host_organization_name":"Indian Institute of Technology Hyderabad","host_organization_lineage":["https://openalex.org/I65181880"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference or Workshop Item"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.4699999988079071,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1785147045","https://openalex.org/W1880262756","https://openalex.org/W1964806982","https://openalex.org/W1983703866","https://openalex.org/W2056030034","https://openalex.org/W2092206588","https://openalex.org/W2103943262","https://openalex.org/W2109624827","https://openalex.org/W2143350951","https://openalex.org/W2156503193","https://openalex.org/W2161050705","https://openalex.org/W6639619044"],"related_works":["https://openalex.org/W2888805565","https://openalex.org/W4312773271","https://openalex.org/W4315588616","https://openalex.org/W2769501189","https://openalex.org/W2962686197","https://openalex.org/W2995939990","https://openalex.org/W2914864478","https://openalex.org/W2402771052","https://openalex.org/W2474958513","https://openalex.org/W2049446342"],"abstract_inverted_index":{"Recent":[0],"years":[1],"have":[2,165],"seen":[3],"a":[4,60,80],"growing":[5],"need":[6,62],"in":[7,44,73],"the":[8,18,45,55,71,74,112,151],"affective":[9],"computing":[10],"community":[11],"to":[12,23,63,82,117],"understand":[13],"an":[14,26],"emotion":[15,27,120,126,143,173],"space":[16,28],"beyond":[17],"seven":[19],"basic":[20,56],"expressions,":[21,57],"leading":[22],"explorations":[24],"of":[25,47,76,114],"continuum":[29,75],"spanned":[30],"by":[31,91],"dimensions":[32],"such":[33],"as":[34,51,122,124],"valence":[35],"and":[36,96,133,139,157,171],"arousal.":[37],"While":[38],"there":[39,58],"has":[40],"been":[41],"substantial":[42],"research":[43],"identification":[46],"facial":[48,66,89,104],"Action":[49],"Units":[50],"building":[52],"blocks":[53],"for":[54,103,142,168],"is":[59],"new":[61],"discover":[64],"fine-grained":[65],"descriptors":[67],"that":[68,131],"can":[69,136],"explain":[70],"variations":[72],"emotions.":[77],"We":[78,129,145],"propose":[79],"methodology":[81],"extract":[83],"Latent":[84,93,98],"Facial":[85],"Topics":[86],"(LFTs)":[87],"from":[88],"videos,":[90],"adapting":[92],"Dirichlet":[94,99],"Allocation":[95,100],"supervised":[97],"topic":[101,115],"models":[102,116],"affect":[105],"analysis.":[106],"In":[107],"this":[108],"work,":[109],"we":[110],"study":[111],"application":[113],"both":[118,169],"discrete":[119,170],"recognition":[121,148,174],"well":[123],"continuous":[125,172],"prediction":[127],"tasks.":[128],"show":[130],"meaningful":[132],"visualizable":[134],"LFTs":[135],"be":[137],"extracted":[138],"used":[140],"successfully":[141],"recognition.":[144],"report":[146],"our":[147],"results":[149],"on":[150],"widely":[152],"known":[153],"Cohn":[154],"Kanade":[155],"Plus":[156],"AVEC":[158],"2012":[159],"FCSC":[160],"challenge":[161],"data":[162],"sets,":[163],"which":[164],"shown":[166],"promise":[167],"problems.":[175]},"counts_by_year":[{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}