{"id":"https://openalex.org/W3132670207","doi":"https://doi.org/10.1109/access.2021.3061744","title":"Happy Emotion Recognition From Unconstrained Videos Using 3D Hybrid Deep Features","display_name":"Happy Emotion Recognition From Unconstrained Videos Using 3D Hybrid Deep Features","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3132670207","doi":"https://doi.org/10.1109/access.2021.3061744","mag":"3132670207"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3061744","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3061744","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09361648.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09361648.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039790126","display_name":"Najmeh Samadiani","orcid":"https://orcid.org/0000-0002-0108-3456"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Najmeh Samadiani","raw_affiliation_strings":["School of Information Technology, Deakin University, Burwood, VIC, Australia","ORCiD"],"affiliations":[{"raw_affiliation_string":"School of Information Technology, Deakin University, Burwood, VIC, Australia","institution_ids":["https://openalex.org/I149704539"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066831688","display_name":"Guangyan Huang","orcid":"https://orcid.org/0000-0002-1821-8644"},"institutions":[{"id":"https://openalex.org/I149704539","display_name":"Deakin University","ror":"https://ror.org/02czsnj07","country_code":"AU","type":"education","lineage":["https://openalex.org/I149704539"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Guangyan Huang","raw_affiliation_strings":["School of Information Technology, Deakin University, Burwood, VIC, Australia","ORCiD"],"affiliations":[{"raw_affiliation_string":"School of Information Technology, Deakin University, Burwood, VIC, Australia","institution_ids":["https://openalex.org/I149704539"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100721270","display_name":"Yu Hu","orcid":"https://orcid.org/0000-0001-8818-4075"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Hu","raw_affiliation_strings":["State Key Laboratory of Computer Architecture, Institute of Computing Technology, University of Chinese Academy of Sciences, Beijing, China","ORCiD"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Computer Architecture, Institute of Computing Technology, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I4210165038"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023380073","display_name":"Xiaowei Li","orcid":"https://orcid.org/0000-0002-0874-814X"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaowei Li","raw_affiliation_strings":["State Key Laboratory of Computer Architecture, Institute of Computing Technology, University of Chinese Academy of Sciences, Beijing, China","ORCiD"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Computer Architecture, Institute of Computing Technology, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I4210165038"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5039790126"],"corresponding_institution_ids":["https://openalex.org/I149704539"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":4.77,"has_fulltext":true,"cited_by_count":28,"citation_normalized_percentile":{"value":0.95107246,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"9","issue":null,"first_page":"35524","last_page":"35538"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9993000030517578,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9987999796867371,"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":0.7259865999221802},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.6132171154022217},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5300341248512268},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4525905251502991},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.43106067180633545},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42122653126716614},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38453739881515503}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7259865999221802},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.6132171154022217},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5300341248512268},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4525905251502991},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.43106067180633545},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42122653126716614},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38453739881515503}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/access.2021.3061744","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3061744","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09361648.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1e1e26a49de349ac83f36074eb0bce6e","is_oa":true,"landing_page_url":"https://doaj.org/article/1e1e26a49de349ac83f36074eb0bce6e","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 35524-35538 (2021)","raw_type":"article"},{"id":"pmh:oai:dro.deakin.edu.au:DU:30149400","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401102","display_name":"Own your potential (DEAKIN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I149704539","host_organization_name":"Deakin University","host_organization_lineage":["https://openalex.org/I149704539"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"},{"id":"pmh:oai:figshare.com:article/20673408","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Happy_emotion_recognition_from_unconstrained_videos_using_3D_hybrid_deep_features/20673408","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3061744","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3061744","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09361648.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7900000214576721,"display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G4700957545","display_name":null,"funder_award_id":"DP190100587","funder_id":"https://openalex.org/F4320334704","funder_display_name":"Australian Research Council"}],"funders":[{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3132670207.pdf","grobid_xml":"https://content.openalex.org/works/W3132670207.grobid-xml"},"referenced_works_count":75,"referenced_works":["https://openalex.org/W1595126664","https://openalex.org/W1596560700","https://openalex.org/W1686810756","https://openalex.org/W1981918162","https://openalex.org/W1999042468","https://openalex.org/W2008933718","https://openalex.org/W2039394285","https://openalex.org/W2078040488","https://openalex.org/W2129106196","https://openalex.org/W2133297572","https://openalex.org/W2139916508","https://openalex.org/W2157653492","https://openalex.org/W2158198839","https://openalex.org/W2183341477","https://openalex.org/W2185532022","https://openalex.org/W2259045471","https://openalex.org/W2277498883","https://openalex.org/W2283758531","https://openalex.org/W2307770531","https://openalex.org/W2338977667","https://openalex.org/W2474193198","https://openalex.org/W2479639417","https://openalex.org/W2546875627","https://openalex.org/W2548899748","https://openalex.org/W2551059751","https://openalex.org/W2576612301","https://openalex.org/W2593621665","https://openalex.org/W2617750261","https://openalex.org/W2738672149","https://openalex.org/W2769039400","https://openalex.org/W2773155012","https://openalex.org/W2790681991","https://openalex.org/W2790687749","https://openalex.org/W2793329641","https://openalex.org/W2800840848","https://openalex.org/W2806792888","https://openalex.org/W2807126412","https://openalex.org/W2888731576","https://openalex.org/W2895359088","https://openalex.org/W2898769710","https://openalex.org/W2901414664","https://openalex.org/W2905628412","https://openalex.org/W2909070361","https://openalex.org/W2911454280","https://openalex.org/W2912159753","https://openalex.org/W2916035981","https://openalex.org/W2938404524","https://openalex.org/W2942454403","https://openalex.org/W2946526173","https://openalex.org/W2949662773","https://openalex.org/W2960453713","https://openalex.org/W2963252191","https://openalex.org/W2963686995","https://openalex.org/W2964350391","https://openalex.org/W2964832281","https://openalex.org/W2971058209","https://openalex.org/W2977259558","https://openalex.org/W2980393359","https://openalex.org/W3003801975","https://openalex.org/W3009319816","https://openalex.org/W3010452544","https://openalex.org/W3016018369","https://openalex.org/W3017142566","https://openalex.org/W3034751874","https://openalex.org/W3043496927","https://openalex.org/W3045605430","https://openalex.org/W3100011500","https://openalex.org/W3104792420","https://openalex.org/W4214724298","https://openalex.org/W4290610135","https://openalex.org/W6637373629","https://openalex.org/W6694260854","https://openalex.org/W6755541679","https://openalex.org/W6773287435","https://openalex.org/W6778907217"],"related_works":["https://openalex.org/W2601157893","https://openalex.org/W2373006798","https://openalex.org/W2131735617","https://openalex.org/W2056912418","https://openalex.org/W2033213769","https://openalex.org/W4312376745","https://openalex.org/W2136016640","https://openalex.org/W2049538278","https://openalex.org/W2886173746","https://openalex.org/W4200043248"],"abstract_inverted_index":{"Facial":[0],"expressions":[1,67],"have":[2,82],"been":[3,83,148],"proven":[4],"to":[5,14,44,93,107,123,177,206,238,246],"be":[6],"the":[7,12,24,95,109,130,139,151,168,179,222,233,252],"most":[8,80],"effective":[9],"way":[10],"for":[11,28,85,99,105,112],"brain":[13],"recognize":[15,124],"human":[16],"emotions":[17,56],"in":[18,31,129,137],"a":[19,118,162,195,229,243],"variety":[20],"of":[21,53,89,141,188],"contexts.":[22],"With":[23],"exponentially":[25],"increasing":[26],"research":[27,42],"emotion":[29,50,70,114,127],"detection":[30],"recent":[32],"years,":[33],"facial":[34,66,217,226,281],"expression":[35,282],"recognition":[36,110],"has":[37,146],"become":[38],"an":[39],"attractive,":[40],"hot":[41],"topic":[43],"identify":[45],"various":[46],"basic":[47,55],"emotions.":[48],"Happy":[49,163],"is":[51,61,103,153,273],"one":[52],"such":[54],"with":[57],"many":[58],"applications,":[59],"which":[60,91],"more":[62,275],"likely":[63],"recognized":[64],"by":[65,181],"than":[68,277],"other":[69],"measurement":[71],"instruments":[72],"(e.g.,":[73,115,235],"audio/speech,":[74],"textual":[75],"and":[76,150,172,183,201,220,228,257],"physiological":[77],"sensing).":[78],"Nowadays,":[79],"methods":[81,120],"developed":[84],"identifying":[86],"multiple":[87],"types":[88,187],"emotions,":[90],"aim":[92],"achieve":[94],"best":[96],"overall":[97],"precision":[98],"all":[100],"emotions;":[101],"it":[102],"hard":[104],"them":[106],"optimize":[108],"accuracy":[111,152,180],"single":[113,125],"happiness).":[116],"Only":[117],"few":[119],"are":[121],"designed":[122],"happy":[126],"captured":[128],"unconstrained":[131,263],"videos;":[132],"however,":[133],"their":[134,240],"limitations":[135],"lie":[136],"that":[138,269],"processing":[140],"severe":[142],"head":[143],"pose":[144],"variations":[145],"not":[147,155],"considered,":[149],"still":[154],"satisfied.":[156],"In":[157],"this":[158],"paper,":[159],"we":[160,193,215],"propose":[161],"Emotion":[164],"Recognition":[165],"model":[166],"using":[167,254],"3D":[169,197],"hybrid":[170,196],"deep":[171,189],"distance":[173,223],"features":[174,210,219],"(HappyER-DDF)":[175],"method":[176,272],"improve":[178],"utilizing":[182],"extracting":[184],"two":[185],"different":[186],"visual":[190],"features.":[191],"First,":[192],"employ":[194],"Inception-ResNet":[198],"neural":[199],"network":[200],"long-short":[202],"term":[203],"memory":[204],"(LSTM)":[205],"extract":[207],"dynamic":[208],"spatial-temporal":[209],"among":[211],"sequential":[212],"frames.":[213],"Second,":[214],"detect":[216],"landmarks\u2019":[218],"calculate":[221],"between":[224],"each":[225],"landmark":[227],"reference":[230],"point":[231],"on":[232,261],"face":[234],"nose":[236],"peak)":[237],"capture":[239],"changes":[241],"when":[242],"person":[244],"starts":[245],"smile":[247],"(or":[248],"laugh).":[249],"We":[250],"implement":[251],"experiments":[253],"both":[255],"feature-level":[256],"decision-level":[258],"fusion":[259],"techniques":[260],"three":[262],"video":[264],"datasets.":[265],"The":[266],"results":[267],"demonstrate":[268],"our":[270],"HappyER-DDF":[271],"arguably":[274],"accurate":[276],"several":[278],"currently":[279],"available":[280],"models.":[283]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":5}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
