{"id":"https://openalex.org/W1988088279","doi":"https://doi.org/10.1145/2512530.2512532","title":"Depression recognition based on dynamic facial and vocal expression features using partial least square regression","display_name":"Depression recognition based on dynamic facial and vocal expression features using partial least square regression","publication_year":2013,"publication_date":"2013-10-17","ids":{"openalex":"https://openalex.org/W1988088279","doi":"https://doi.org/10.1145/2512530.2512532","mag":"1988088279"},"language":"en","primary_location":{"id":"doi:10.1145/2512530.2512532","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2512530.2512532","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd ACM international workshop on Audio/visual emotion challenge","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/A5108055798","display_name":"Hongying Meng","orcid":"https://orcid.org/0000-0002-8836-1382"},"institutions":[{"id":"https://openalex.org/I59433898","display_name":"Brunel University of London","ror":"https://ror.org/00dn4t376","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I59433898"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Hongying Meng","raw_affiliation_strings":["Brunel University, Uxbridge, UB8 3PH, United Kingdom","Brunel University, Uxbridge UB8 3PH, UNITED KINGDOM#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Brunel University, Uxbridge, UB8 3PH, United Kingdom","institution_ids":["https://openalex.org/I59433898"]},{"raw_affiliation_string":"Brunel University, Uxbridge UB8 3PH, UNITED KINGDOM#TAB#","institution_ids":["https://openalex.org/I59433898"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056972984","display_name":"Di Huang","orcid":"https://orcid.org/0000-0002-2412-9330"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Di Huang","raw_affiliation_strings":["Beihang University, Beijing, China","BeiHang University, BeiJing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"BeiHang University, BeiJing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100453983","display_name":"Heng Wang","orcid":"https://orcid.org/0000-0003-2597-4648"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heng Wang","raw_affiliation_strings":["Beihang University, Beijing, China","BeiHang University, BeiJing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"BeiHang University, BeiJing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057118376","display_name":"Hongyu Yang","orcid":"https://orcid.org/0000-0002-6955-2503"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyu Yang","raw_affiliation_strings":["Beihang University, Beijing, China","BeiHang University, BeiJing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"BeiHang University, BeiJing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065609180","display_name":"Mohammed AI-Shuraifi","orcid":null},"institutions":[{"id":"https://openalex.org/I59433898","display_name":"Brunel University of London","ror":"https://ror.org/00dn4t376","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I59433898"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mohammed AI-Shuraifi","raw_affiliation_strings":["Brunel University, Uxbridge, UB8 3PH, United Kingdom","Brunel University, Uxbridge UB8 3PH, UNITED KINGDOM#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Brunel University, Uxbridge, UB8 3PH, United Kingdom","institution_ids":["https://openalex.org/I59433898"]},{"raw_affiliation_string":"Brunel University, Uxbridge UB8 3PH, UNITED KINGDOM#TAB#","institution_ids":["https://openalex.org/I59433898"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100398953","display_name":"Yunhong Wang","orcid":"https://orcid.org/0000-0001-8001-2703"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunhong Wang","raw_affiliation_strings":["Beihang University, Beijing, China","BeiHang University, BeiJing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"BeiHang University, BeiJing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":220,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"21","last_page":"30"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9753000140190125,"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/T10057","display_name":"Face and Expression Recognition","score":0.9549999833106995,"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/facial-expression","display_name":"Facial expression","score":0.6416256427764893},{"id":"https://openalex.org/keywords/mood","display_name":"Mood","score":0.6220656633377075},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.564393937587738},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5436280965805054},{"id":"https://openalex.org/keywords/depression","display_name":"Depression (economics)","score":0.5422897934913635},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.5381177067756653},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5097183585166931},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.5060402750968933},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49770262837409973},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.48749446868896484},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4814835786819458},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.4491644501686096},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.4365333914756775},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3742610216140747},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36560487747192383},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.3291008770465851},{"id":"https://openalex.org/keywords/clinical-psychology","display_name":"Clinical psychology","score":0.23675742745399475},{"id":"https://openalex.org/keywords/psychotherapist","display_name":"Psychotherapist","score":0.11638489365577698}],"concepts":[{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.6416256427764893},{"id":"https://openalex.org/C2780733359","wikidata":"https://www.wikidata.org/wiki/Q331769","display_name":"Mood","level":2,"score":0.6220656633377075},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.564393937587738},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5436280965805054},{"id":"https://openalex.org/C2776867660","wikidata":"https://www.wikidata.org/wiki/Q1814941","display_name":"Depression (economics)","level":2,"score":0.5422897934913635},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.5381177067756653},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5097183585166931},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.5060402750968933},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49770262837409973},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.48749446868896484},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4814835786819458},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.4491644501686096},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.4365333914756775},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3742610216140747},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36560487747192383},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.3291008770465851},{"id":"https://openalex.org/C70410870","wikidata":"https://www.wikidata.org/wiki/Q199906","display_name":"Clinical psychology","level":1,"score":0.23675742745399475},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.11638489365577698},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2512530.2512532","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2512530.2512532","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd ACM international workshop on Audio/visual emotion challenge","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6100000143051147,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W166500168","https://openalex.org/W1500929076","https://openalex.org/W1508960934","https://openalex.org/W1588539311","https://openalex.org/W1626978984","https://openalex.org/W1628541567","https://openalex.org/W1964469912","https://openalex.org/W1976066595","https://openalex.org/W1976251851","https://openalex.org/W1981231682","https://openalex.org/W1993551758","https://openalex.org/W2006217447","https://openalex.org/W2074788634","https://openalex.org/W2077684629","https://openalex.org/W2092206588","https://openalex.org/W2096108608","https://openalex.org/W2105020570","https://openalex.org/W2105198535","https://openalex.org/W2106390385","https://openalex.org/W2107865346","https://openalex.org/W2108072369","https://openalex.org/W2108445559","https://openalex.org/W2109138290","https://openalex.org/W2109774206","https://openalex.org/W2110840966","https://openalex.org/W2110885456","https://openalex.org/W2111926505","https://openalex.org/W2122675580","https://openalex.org/W2123861288","https://openalex.org/W2129106196","https://openalex.org/W2130162821","https://openalex.org/W2136119880","https://openalex.org/W2143350951","https://openalex.org/W2145310492","https://openalex.org/W2154716422","https://openalex.org/W2157735101","https://openalex.org/W2159017231","https://openalex.org/W2161969291","https://openalex.org/W2162574641","https://openalex.org/W2163352848","https://openalex.org/W2163808566","https://openalex.org/W2163928333","https://openalex.org/W2165715280","https://openalex.org/W2168341643","https://openalex.org/W2307710359","https://openalex.org/W2603247401","https://openalex.org/W4253024038","https://openalex.org/W6606747371","https://openalex.org/W6630486035","https://openalex.org/W6635087628"],"related_works":["https://openalex.org/W73545470","https://openalex.org/W4224266612","https://openalex.org/W2383394264","https://openalex.org/W4320153225","https://openalex.org/W4293261942","https://openalex.org/W3125968744","https://openalex.org/W2167701463","https://openalex.org/W2110287964","https://openalex.org/W4307407935","https://openalex.org/W649759291"],"abstract_inverted_index":{"Depression":[0],"is":[1,123,168],"a":[2,40,63],"typical":[3],"mood":[4],"disorder,":[5],"and":[6,20,47,70,73,93,104,133,139,153,174,181],"the":[7,16,44,55,76,88,110,116,127,130,142,171,189],"persons":[8],"who":[9],"are":[10,156],"often":[11],"in":[12,18,33,57,102],"this":[13],"state":[14],"face":[15],"risk":[17],"mental":[19],"even":[21],"physical":[22],"problems.":[23],"In":[24,38],"recent":[25],"years,":[26],"there":[27],"has":[28],"therefore":[29],"been":[30],"increasing":[31],"attention":[32],"machine":[34],"based":[35],"depression":[36,134,143],"analysis.":[37],"such":[39],"low":[41],"mood,":[42],"both":[43],"facial":[45,103],"expression":[46,106],"voice":[48],"of":[49,78,99,107,151],"human":[50],"beings":[51],"appear":[52],"different":[53],"from":[54,90],"ones":[56],"normal":[58],"states.":[59],"This":[60],"paper":[61],"presents":[62],"novel":[64],"method,":[65],"which":[66],"comprehensively":[67],"models":[68],"visual":[69,152],"vocal":[71,105,154],"modalities,":[72],"automatically":[74],"predicts":[75],"scale":[77,144],"depression.":[79,108],"On":[80,109],"one":[81],"hand,":[82,112],"Motion":[83],"History":[84],"Histogram":[85],"(MHH)":[86],"extracts":[87],"dynamics":[89],"corresponding":[91],"video":[92],"audio":[94],"data":[95],"to":[96,125],"represent":[97],"characteristics":[98],"subtle":[100],"changes":[101],"other":[111],"for":[113,145,162],"each":[114],"modality,":[115],"Partial":[117],"Least":[118],"Square":[119],"(PLS)":[120],"regression":[121],"algorithm":[122],"applied":[124],"learn":[126],"relationship":[128],"between":[129],"dynamic":[131],"features":[132],"scales":[135],"using":[136],"training":[137],"data,":[138],"then":[140],"predict":[141],"an":[146],"unseen":[147],"one.":[148],"Predicted":[149],"values":[150],"clues":[155],"further":[157],"combined":[158],"at":[159],"decision":[160],"level":[161],"final":[163],"decision.":[164],"The":[165],"proposed":[166],"approach":[167],"evaluated":[169],"on":[170],"AVEC2013":[172,190],"dataset":[173],"experimental":[175],"results":[176,186],"clearly":[177],"highlight":[178],"its":[179],"effectiveness":[180],"better":[182],"performance":[183],"than":[184],"baseline":[185],"provided":[187],"by":[188],"challenge":[191],"organiser.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":25},{"year":2024,"cited_by_count":24},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":23},{"year":2021,"cited_by_count":20},{"year":2020,"cited_by_count":19},{"year":2019,"cited_by_count":22},{"year":2018,"cited_by_count":13},{"year":2017,"cited_by_count":15},{"year":2016,"cited_by_count":9},{"year":2015,"cited_by_count":18},{"year":2014,"cited_by_count":12}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
