{"id":"https://openalex.org/W7143498677","doi":"https://doi.org/10.1109/access.2026.3679073","title":"Multi-Grained Gesture Modeling for Emotion Recognition","display_name":"Multi-Grained Gesture Modeling for Emotion Recognition","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7143498677","doi":"https://doi.org/10.1109/access.2026.3679073"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3679073","doi":"https://doi.org/10.1109/access.2026.3679073","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3679073","pdf_url":null,"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,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","oarl","poland-100","russia-white-list-1","vabb-shw"],"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"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3679073","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130984563","display_name":"Rong Wei","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4405271159","display_name":"Hubei University of Police","ror":"https://ror.org/01zdqrx48","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405271159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rong Wei","raw_affiliation_strings":["Department of Information Technology, Hubei University of Police, Wuhan, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Technology, Hubei University of Police, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I4405271159"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076785434","display_name":"Xuepeng Huang","orcid":"https://orcid.org/0000-0002-3705-6281","observed_orcids":["https://orcid.org/0000-0002-3705-6281"]},"institutions":[{"id":"https://openalex.org/I4405271159","display_name":"Hubei University of Police","ror":"https://ror.org/01zdqrx48","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405271159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuepeng Huang","raw_affiliation_strings":["Department of Information Technology, Hubei University of Police, Wuhan, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Technology, Hubei University of Police, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I4405271159"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4405271159"],"apc_list":{"value":2075,"currency":"USD","value_usd":2075},"apc_paid":{"value":2075,"currency":"USD","value_usd":2075},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"67046","last_page":"67059"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.7836999893188477,"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"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.7836999893188477,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.12839999794960022,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.07109999656677246,"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/key-frame-extraction","display_name":"key frame extraction","score":0.847000002861023},{"id":"https://openalex.org/keywords/action-context","display_name":"action context","score":0.3490000069141388},{"id":"https://openalex.org/keywords/depth-sensors","display_name":"depth sensors","score":0.3149999976158142}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.775600016117096},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.6295999884605408},{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.538100004196167},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.527999997138977},{"id":"https://openalex.org/C159437735","wikidata":"https://www.wikidata.org/wiki/Q1519524","display_name":"Gesture recognition","level":3,"score":0.525600016117096},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45170000195503235},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3601999878883362},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3481999933719635},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3262999951839447},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30709999799728394},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2957000136375427},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.26660001277923584}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3679073","doi":"https://doi.org/10.1109/access.2026.3679073","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3679073","pdf_url":null,"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,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","oarl","poland-100","russia-white-list-1","vabb-shw"],"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:7264203afdaf47c6b7963397415dad27","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/7264203afdaf47c6b7963397415dad27","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"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 14, Pp 67046-67059 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3679073","doi":"https://doi.org/10.1109/access.2026.3679073","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3679073","pdf_url":null,"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,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","oarl","poland-100","russia-white-list-1","vabb-shw"],"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":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320326699","display_name":"Ministry of Public Security of the People's Republic of China","ror":"https://ror.org/00bt9we26"},{"id":"https://openalex.org/F4320328700","display_name":"Hubei University of Police","ror":"https://ror.org/01zdqrx48"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W764651262","https://openalex.org/W846669277","https://openalex.org/W1950788856","https://openalex.org/W1979378996","https://openalex.org/W1983592444","https://openalex.org/W2030061193","https://openalex.org/W2048821851","https://openalex.org/W2072028093","https://openalex.org/W2073139398","https://openalex.org/W2092030178","https://openalex.org/W2114826417","https://openalex.org/W2128679772","https://openalex.org/W2132680170","https://openalex.org/W2138460106","https://openalex.org/W2143004591","https://openalex.org/W2144380653","https://openalex.org/W2145546283","https://openalex.org/W2158787690","https://openalex.org/W2294987501","https://openalex.org/W2405955809","https://openalex.org/W2472901858","https://openalex.org/W2510185399","https://openalex.org/W2606294640","https://openalex.org/W2626778328","https://openalex.org/W2795354662","https://openalex.org/W2803158089","https://openalex.org/W2947229206","https://openalex.org/W2952587893","https://openalex.org/W2954818883","https://openalex.org/W2963531836","https://openalex.org/W2964134613","https://openalex.org/W2991276178","https://openalex.org/W3008809756","https://openalex.org/W3029821368","https://openalex.org/W3084083256","https://openalex.org/W3085139254","https://openalex.org/W3109225549","https://openalex.org/W3177365697","https://openalex.org/W3179427928","https://openalex.org/W3184613951","https://openalex.org/W3203634062","https://openalex.org/W4205653891","https://openalex.org/W4206947770","https://openalex.org/W4210674019","https://openalex.org/W4285597462","https://openalex.org/W4378907171","https://openalex.org/W4405778915","https://openalex.org/W4414650542","https://openalex.org/W4414781662","https://openalex.org/W4417122444"],"related_works":["https://openalex.org/W2904553342","https://openalex.org/W2970408855","https://openalex.org/W2333212123","https://openalex.org/W4377693936","https://openalex.org/W7043844917","https://openalex.org/W3121276084","https://openalex.org/W3190458516","https://openalex.org/W1689644917","https://openalex.org/W4288778768","https://openalex.org/W2954818883"],"abstract_inverted_index":{"In":[0,219],"recent":[1],"years,":[2],"emotion":[3,81,196,224],"recognition":[4,49,82],"from":[5,199],"body":[6],"gesture":[7,48,80,103,223],"movements":[8],"has":[9],"become":[10],"an":[11,78,106],"important":[12,107],"research":[13],"field":[14],"with":[15],"the":[16,30,52,58,72,100,119,154,163,169,177,195,200,210,217,220,232],"continuous":[17,36],"development":[18],"and":[19,24,39,92,104,129,161,172,204,212],"improvement":[20],"of":[21,29,35,88,102,121,140,197,202,222],"depth":[22],"sensors":[23],"computer":[25],"vision":[26],"algorithms.":[27],"Most":[28],"public":[31,186],"datasets":[32,160,187],"are":[33],"records":[34],"emotional":[37],"actions,":[38],"frame":[40,42,111],"by":[41,216],"analysis":[43],"or":[44],"as":[45],"a":[46,143],"single":[47],"will":[50],"ignore":[51],"context":[53],"relationship":[54],"between":[55],"actions.":[56],"Thus,":[57],"method":[59,152,227],"based":[60],"on":[61,67,118,184],"manual":[62],"feature":[63],"extraction":[64],"performs":[65],"poorly":[66],"large-scale":[68],"datasets.":[69],"To":[70],"solve":[71],"above":[73],"problems,":[74],"this":[75],"paper":[76],"proposes":[77],"effective":[79],"model.":[83,94],"The":[84,95,113,180],"model":[85,91,98,115,207],"is":[86,116,191,228],"composed":[87],"pseudo":[89,96],"energy":[90,97,101,203],"multi-grained":[93,114,206],"quantifies":[99],"provides":[105,126,133],"basis":[108,120],"for":[109],"key":[110],"extraction.":[112],"proposed":[117],"both":[122],"fine":[123],"grained":[124,131],"which":[125,132],"specific":[127],"information":[128],"coarse":[130],"logical":[134],"information.":[135],"By":[136],"integrating":[137],"multiple":[138],"levels":[139],"granularity":[141],"into":[142],"unified":[144],"architecture,":[145],"we":[146],"demonstrate":[147],"enhanced":[148],"classification":[149,166,174],"performance.":[150],"Our":[151],"surpasses":[153],"prior":[155],"state-of-the-art":[156,233],"approaches":[157],"in":[158,168,176],"two":[159,185],"achieves":[162],"highest":[164],"82.7%":[165],"accuracy":[167,175],"KDAE":[170],"dataset":[171],"80.6%":[173],"EMBG":[178],"dataset.":[179],"excellent":[181],"experimental":[182],"results":[183],"show":[188],"that":[189],"it":[190],"feasible":[192],"to":[193,208,231],"divide":[194],"action":[198],"perspective":[201],"use":[205],"provide":[209],"low-level":[211],"high-level":[213],"features":[214],"required":[215],"network.":[218],"task":[221],"recognition,":[225],"our":[226],"obviously":[229],"superior":[230],"methods.":[234]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-03-31T00:00:00"}
