{"id":"https://openalex.org/W2898901496","doi":"https://doi.org/10.1109/cbmi.2018.8516497","title":"Towards Independent Stress Detection: A Dependent Model Using Facial Action Units","display_name":"Towards Independent Stress Detection: A Dependent Model Using Facial Action Units","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2898901496","doi":"https://doi.org/10.1109/cbmi.2018.8516497","mag":"2898901496"},"language":"en","primary_location":{"id":"doi:10.1109/cbmi.2018.8516497","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cbmi.2018.8516497","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Conference on Content-Based Multimedia Indexing (CBMI)","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/A5015231548","display_name":"Carla Viegas","orcid":"https://orcid.org/0000-0002-1545-6479"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Carla Viegas","raw_affiliation_strings":["Language Technologies Institute, Carnegie Mellon University Universidade NOVA Lisboa, Pittsburgh, USA"],"affiliations":[{"raw_affiliation_string":"Language Technologies Institute, Carnegie Mellon University Universidade NOVA Lisboa, Pittsburgh, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103433414","display_name":"Shing-hon Lau","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shing-Hon Lau","raw_affiliation_strings":["Machine Learning Department, Carnegie Mellon University, Pittsburgh, USA"],"affiliations":[{"raw_affiliation_string":"Machine Learning Department, Carnegie Mellon University, Pittsburgh, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068712049","display_name":"Roy A. Maxion","orcid":"https://orcid.org/0000-0002-2833-7276"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Roy Maxion","raw_affiliation_strings":["Machine Learning Department, Carnegie Mellon University, Pittsburgh, USA"],"affiliations":[{"raw_affiliation_string":"Machine Learning Department, Carnegie Mellon University, Pittsburgh, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103099928","display_name":"Alexander G. Hauptmann","orcid":"https://orcid.org/0000-0003-2123-0684"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexander Hauptmann","raw_affiliation_strings":["Language Technologies Institute, Carnegie Mellon University Universidade NOVA Lisboa, Pittsburgh, USA"],"affiliations":[{"raw_affiliation_string":"Language Technologies Institute, Carnegie Mellon University Universidade NOVA Lisboa, Pittsburgh, USA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5015231548"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":1.8437,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":{"value":0.85934975,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"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":0.9994999766349792,"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":0.9994999766349792,"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/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.9729999899864197,"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/T10263","display_name":"Eating Disorders and Behaviors","score":0.9664999842643738,"subfield":{"id":"https://openalex.org/subfields/3203","display_name":"Clinical Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.6966780424118042},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6928368210792542},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.622514009475708},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.586277186870575},{"id":"https://openalex.org/keywords/anger","display_name":"Anger","score":0.5418902039527893},{"id":"https://openalex.org/keywords/stress","display_name":"Stress (linguistics)","score":0.5344454646110535},{"id":"https://openalex.org/keywords/stressor","display_name":"Stressor","score":0.4742514193058014},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.4463210105895996},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.42173415422439575},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4210779666900635},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4192464351654053},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33205467462539673},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.23182135820388794},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.11154145002365112},{"id":"https://openalex.org/keywords/clinical-psychology","display_name":"Clinical psychology","score":0.09955069422721863}],"concepts":[{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.6966780424118042},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6928368210792542},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.622514009475708},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.586277186870575},{"id":"https://openalex.org/C2779302386","wikidata":"https://www.wikidata.org/wiki/Q79871","display_name":"Anger","level":2,"score":0.5418902039527893},{"id":"https://openalex.org/C21036866","wikidata":"https://www.wikidata.org/wiki/Q181767","display_name":"Stress (linguistics)","level":2,"score":0.5344454646110535},{"id":"https://openalex.org/C125370674","wikidata":"https://www.wikidata.org/wiki/Q1527480","display_name":"Stressor","level":2,"score":0.4742514193058014},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.4463210105895996},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.42173415422439575},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4210779666900635},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4192464351654053},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33205467462539673},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.23182135820388794},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.11154145002365112},{"id":"https://openalex.org/C70410870","wikidata":"https://www.wikidata.org/wiki/Q199906","display_name":"Clinical psychology","level":1,"score":0.09955069422721863},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cbmi.2018.8516497","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cbmi.2018.8516497","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 International Conference on Content-Based Multimedia Indexing (CBMI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1912166081","https://openalex.org/W1921929190","https://openalex.org/W1932783937","https://openalex.org/W2068975495","https://openalex.org/W2073738449","https://openalex.org/W2103943262","https://openalex.org/W2105036571","https://openalex.org/W2112757439","https://openalex.org/W2117866167","https://openalex.org/W2136466671","https://openalex.org/W2167801237","https://openalex.org/W2171801645","https://openalex.org/W2187089797","https://openalex.org/W2395639500","https://openalex.org/W2474755898","https://openalex.org/W2603578650","https://openalex.org/W2608703442","https://openalex.org/W2743283820","https://openalex.org/W2750953686","https://openalex.org/W2752392113","https://openalex.org/W2770802215","https://openalex.org/W2791748249","https://openalex.org/W2977392341","https://openalex.org/W3098017922","https://openalex.org/W3170706636","https://openalex.org/W4235421565","https://openalex.org/W6640174009","https://openalex.org/W6741805837","https://openalex.org/W6745692948","https://openalex.org/W6749005119","https://openalex.org/W6768975301"],"related_works":["https://openalex.org/W2531159956","https://openalex.org/W2000785801","https://openalex.org/W986318368","https://openalex.org/W2158625435","https://openalex.org/W1968844886","https://openalex.org/W2030507284","https://openalex.org/W2060991067","https://openalex.org/W2087919909","https://openalex.org/W2384410913","https://openalex.org/W2352878646"],"abstract_inverted_index":{"Our":[0],"society":[1],"is":[2],"increasingly":[3],"more":[4,83],"susceptible":[5],"to":[6,17,25,28,44,54,93,129,154,183,189],"chronic":[7],"stress.":[8],"Reasons":[9],"are":[10,213],"daily":[11],"worries,":[12],"workload,":[13],"and":[14,30,60,152,180,195],"the":[15,36,101,118,139,206,216],"wish":[16],"fulfil":[18],"a":[19,82,108,155,158,229],"myriad":[20],"of":[21,77,103,111,120,187],"expectations.":[22],"Unfortunately,":[23],"long-exposure":[24],"stress":[26,46,78,96,211],"leads":[27],"physical":[29],"mental":[31],"health":[32],"problems.":[33],"To":[34],"avoid":[35],"described":[37],"consequences,":[38],"mobile":[39],"applications":[40],"have":[41,68,90],"been":[42,91],"studied":[43],"track":[45],"in":[47,176,191,197,223],"combination":[48],"with":[49,162],"wearables.":[50],"However,":[51],"wearables":[52],"need":[53],"be":[55,62,81],"worn":[56],"all":[57,219],"day":[58],"long":[59,136],"can":[61],"costly.":[63],"Given":[64],"that":[65,205],"most":[66,208],"laptops":[67],"inbuilt":[69],"cameras,":[70],"using":[71,169,226],"video":[72,178],"data":[73],"for":[74,210,218],"personal":[75],"tracking":[76],"levels":[79],"could":[80],"affordable":[84],"alternative.":[85],"In":[86,114],"previous":[87,224],"work,":[88,225],"videos":[89,137,146],"used":[92,133],"detect":[94],"cognitive":[95],"during":[97,235],"driving":[98],"by":[99,142],"measuring":[100],"presence":[102],"anger":[104],"or":[105],"fear":[106],"through":[107],"limited":[109],"number":[110],"facial":[112,122,227],"expressions.":[113],"contrast,":[115],"we":[116],"propose":[117],"use":[119],"17":[121],"action":[123],"units":[124],"(AUs)":[125],"not":[126,214],"solely":[127],"restricted":[128],"those":[130],"emotions.":[131],"We":[132,165],"five":[134],"one-hour":[135],"from":[138],"dataset":[140],"collected":[141],"Lau":[143],"[1].":[144],"The":[145],"show":[147],"subjects":[148],"while":[149],"typing,":[150],"resting,":[151],"exposed":[153],"stressor,":[156],"being":[157],"multitasking":[159],"exercise":[160],"combined":[161],"social":[163],"evaluation.":[164],"performed":[166],"binary":[167],"classification":[168,194],"several":[170],"simple":[171],"classifiers":[172],"on":[173],"AUs":[174,207],"extracted":[175],"each":[177],"frame":[179],"were":[181],"able":[182],"achieve":[184],"an":[185],"accuracy":[186],"up":[188],"74%":[190],"subject":[192,198],"independent":[193],"91%":[196],"dependent":[199],"classification.":[200,236],"These":[201],"preliminary":[202],"results":[203],"indicate":[204],"relevant":[209],"detection":[212],"consistently":[215],"same":[217],"5":[220],"subjects.":[221],"Also":[222],"cues,":[228],"strong":[230],"person-specific":[231],"component":[232],"was":[233],"found":[234]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}