{"id":"https://openalex.org/W1983703866","doi":"https://doi.org/10.1145/2388676.2388783","title":"Robust continuous prediction of human emotions using multiscale dynamic cues","display_name":"Robust continuous prediction of human emotions using multiscale dynamic cues","publication_year":2012,"publication_date":"2012-10-22","ids":{"openalex":"https://openalex.org/W1983703866","doi":"https://doi.org/10.1145/2388676.2388783","mag":"1983703866"},"language":"en","primary_location":{"id":"doi:10.1145/2388676.2388783","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2388676.2388783","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th ACM international conference on Multimodal interaction","raw_type":"proceedings-article"},"type":"preprint","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/A5054982466","display_name":"J\u00e9r\u00e9mie Nicolle","orcid":null},"institutions":[{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"J\u00e9r\u00e9mie Nicolle","raw_affiliation_strings":["Universit\u00e8 Pierre & Marie Curie, Paris, France"],"affiliations":[{"raw_affiliation_string":"Universit\u00e8 Pierre & Marie Curie, Paris, France","institution_ids":["https://openalex.org/I39804081"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050604008","display_name":"Vincent Rapp","orcid":null},"institutions":[{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Vincent Rapp","raw_affiliation_strings":["Universit\u00e8 Pierre & Marie Curie, Paris, France"],"affiliations":[{"raw_affiliation_string":"Universit\u00e8 Pierre & Marie Curie, Paris, France","institution_ids":["https://openalex.org/I39804081"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022871131","display_name":"K\u00e9vin Bailly","orcid":"https://orcid.org/0000-0001-7802-3673"},"institutions":[{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"K\u00e9vin Bailly","raw_affiliation_strings":["Universit\u00e8 Pierre & Marie Curie, Paris, France"],"affiliations":[{"raw_affiliation_string":"Universit\u00e8 Pierre & Marie Curie, Paris, France","institution_ids":["https://openalex.org/I39804081"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045983846","display_name":"Lionel Pr\u00e9vost","orcid":null},"institutions":[{"id":"https://openalex.org/I52585520","display_name":"Universit\u00e9 des Antilles","ror":"https://ror.org/02ryfmr77","country_code":"GP","type":"education","lineage":["https://openalex.org/I52585520"]}],"countries":["GP"],"is_corresponding":false,"raw_author_name":"Lionel Prevost","raw_affiliation_strings":["Universit\u00e8 of French West Indies & Guiana, Guadeloupe, France"],"affiliations":[{"raw_affiliation_string":"Universit\u00e8 of French West Indies & Guiana, Guadeloupe, France","institution_ids":["https://openalex.org/I52585520"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049398785","display_name":"Mohamed Ch\u00e9touani","orcid":"https://orcid.org/0000-0002-2920-4539"},"institutions":[{"id":"https://openalex.org/I39804081","display_name":"Sorbonne Universit\u00e9","ror":"https://ror.org/02en5vm52","country_code":"FR","type":"education","lineage":["https://openalex.org/I39804081"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Mohamed Chetouani","raw_affiliation_strings":["Universit\u00e8 Pierre & Marie Curie, Paris, France"],"affiliations":[{"raw_affiliation_string":"Universit\u00e8 Pierre & Marie Curie, Paris, France","institution_ids":["https://openalex.org/I39804081"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5054982466"],"corresponding_institution_ids":["https://openalex.org/I39804081"],"apc_list":null,"apc_paid":null,"fwci":12.7564,"has_fulltext":false,"cited_by_count":109,"citation_normalized_percentile":{"value":0.98930601,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"501","last_page":"508"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9987999796867371,"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":0.9987999796867371,"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/T10057","display_name":"Face and Expression Recognition","score":0.9972000122070312,"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/T10860","display_name":"Speech and Audio Processing","score":0.9941999912261963,"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/computer-science","display_name":"Computer science","score":0.7800378799438477},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5775237083435059},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5672791600227356},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.43820828199386597},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43059438467025757},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4274980127811432},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41807055473327637},{"id":"https://openalex.org/keywords/merge","display_name":"Merge (version control)","score":0.4118395149707794},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.37742528319358826}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7800378799438477},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5775237083435059},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5672791600227356},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.43820828199386597},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43059438467025757},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4274980127811432},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41807055473327637},{"id":"https://openalex.org/C197129107","wikidata":"https://www.wikidata.org/wiki/Q1921621","display_name":"Merge (version control)","level":2,"score":0.4118395149707794},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.37742528319358826},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/2388676.2388783","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2388676.2388783","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th ACM international conference on Multimodal interaction","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.433.2139","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.433.2139","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.isir.upmc.fr/files/2012ACTI2511.pdf","raw_type":"text"},{"id":"pmh:oai:HAL:hal-02423171v1","is_oa":false,"landing_page_url":"https://hal.sorbonne-universite.fr/hal-02423171","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the 14th ACM international conference on Multimodal interaction (ICMI'12), Oct 2012, Santa Monica, United States. pp.501, ⟨10.1145/2388676.2388783⟩","raw_type":"Conference papers"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W158626325","https://openalex.org/W160639499","https://openalex.org/W177655890","https://openalex.org/W1511113019","https://openalex.org/W1589514602","https://openalex.org/W1971713783","https://openalex.org/W1971737742","https://openalex.org/W1975436731","https://openalex.org/W2026243162","https://openalex.org/W2033702744","https://openalex.org/W2076017598","https://openalex.org/W2092206588","https://openalex.org/W2113507809","https://openalex.org/W2119802788","https://openalex.org/W2130162821","https://openalex.org/W2135776491","https://openalex.org/W2143899944","https://openalex.org/W2144961093","https://openalex.org/W2156848952","https://openalex.org/W2169166781","https://openalex.org/W2219827282","https://openalex.org/W2268421884","https://openalex.org/W2599280577","https://openalex.org/W3097096317","https://openalex.org/W4319068731"],"related_works":["https://openalex.org/W2185469136","https://openalex.org/W4234886518","https://openalex.org/W2011264131","https://openalex.org/W2389591058","https://openalex.org/W2382112581","https://openalex.org/W3124036233","https://openalex.org/W4229787472","https://openalex.org/W4306353150","https://openalex.org/W2026860389","https://openalex.org/W2486541857"],"abstract_inverted_index":{"Designing":[0],"systems":[1,152],"able":[2],"to":[3,28,33,41,50,72,110,150],"interact":[4],"with":[5,97],"humans":[6],"in":[7],"a":[8,12,94,104,111,120,128,144],"natural":[9,23],"manner":[10],"is":[11,25,49],"complex":[13],"and":[14,30,63,81,90,134,137,170],"far":[15],"from":[16],"solved":[17],"problem.":[18],"A":[19],"key":[20,164],"aspect":[21],"of":[22,77,162,166],"interaction":[24],"the":[26,42,132,135,160,167],"ability":[27],"understand":[29],"appropriately":[31],"respond":[32],"human":[34,57],"emotions.":[35],"This":[36],"paper":[37],"details":[38],"our":[39],"response":[40],"Audio/Visual":[43],"Emotion":[44],"Challenge":[45],"(AVEC'12)":[46],"whose":[47],"goal":[48],"continuously":[51],"predict":[52],"four":[53],"affective":[54],"signals":[55,78],"describing":[56],"emotions":[58],"(namely":[59],"valence,":[60],"arousal,":[61],"expectancy":[62],"power).":[64],"The":[65],"proposed":[66,168],"method":[67,169],"uses":[68],"log-magnitude":[69],"Fourier":[70],"spectra":[71],"extract":[73],"multiscale":[74],"dynamic":[75],"descriptions":[76],"characterizing":[79],"global":[80],"local":[82],"face":[83],"appearance":[84],"as":[85,87],"well":[86],"head":[88],"movements":[89],"voice.":[91],"We":[92,141],"perform":[93],"kernel":[95],"regression":[96],"very":[98,173],"few":[99],"representative":[100],"samples":[101],"selected":[102],"via":[103],"supervised":[105],"weighted-distance-based":[106],"clustering,":[107],"that":[108,124],"leads":[109],"high":[112],"generalization":[113],"power.":[114],"For":[115],"selecting":[116],"features,":[117],"we":[118,171],"introduce":[119],"new":[121],"correlation-based":[122],"measure":[123],"takes":[125],"into":[126],"account":[127],"possible":[129],"delay":[130],"between":[131],"labels":[133],"data":[136],"significantly":[138],"increases":[139],"robustness.":[140],"also":[142],"propose":[143],"particularly":[145],"fast":[146],"regressor-level":[147],"fusion":[148],"framework":[149],"merge":[151],"based":[153],"on":[154],"different":[155],"modalities.":[156],"Experiments":[157],"have":[158],"proven":[159],"efficiency":[161],"each":[163],"point":[165],"obtain":[172],"promising":[174],"results.":[175]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":11},{"year":2018,"cited_by_count":12},{"year":2017,"cited_by_count":10},{"year":2016,"cited_by_count":10},{"year":2015,"cited_by_count":17},{"year":2014,"cited_by_count":15},{"year":2013,"cited_by_count":12}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}