{"id":"https://openalex.org/W2909655403","doi":"https://doi.org/10.1145/3318299.3318321","title":"Human Emotion Recognition in Video Using Subtraction Pre-Processing","display_name":"Human Emotion Recognition in Video Using Subtraction Pre-Processing","publication_year":2019,"publication_date":"2019-02-22","ids":{"openalex":"https://openalex.org/W2909655403","doi":"https://doi.org/10.1145/3318299.3318321","mag":"2909655403"},"language":"en","primary_location":{"id":"doi:10.1145/3318299.3318321","doi":"https://doi.org/10.1145/3318299.3318321","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3318299.3318321","pdf_url":null,"source":{"id":"https://openalex.org/S7407088508","display_name":"International Conference on Machine Learning and Computing (ICMLC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 11th International Conference on Machine Learning and Computing","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5102830244","display_name":"Zhihao He","orcid":"https://orcid.org/0009-0008-2695-137X","observed_orcids":["https://orcid.org/0009-0008-2695-137X"]},"institutions":[{"id":"https://openalex.org/I181647926","display_name":"University of Strathclyde","ror":"https://ror.org/00n3w3b69","country_code":"GB","type":"education","lineage":["https://openalex.org/I181647926"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Zhihao He","raw_affiliation_strings":["CeSIP, Royal College Building, University of Strathclyde, Glasgow"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CeSIP, Royal College Building, University of Strathclyde, Glasgow","institution_ids":["https://openalex.org/I181647926"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073863021","display_name":"Jin Wen Tian","orcid":"https://orcid.org/0000-0001-5313-1600","observed_orcids":["https://orcid.org/0000-0001-5313-1600"]},"institutions":[{"id":"https://openalex.org/I181647926","display_name":"University of Strathclyde","ror":"https://ror.org/00n3w3b69","country_code":"GB","type":"education","lineage":["https://openalex.org/I181647926"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Tian Jin","raw_affiliation_strings":["CeSIP, Royal College Building, University of Strathclyde, Glasgow"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CeSIP, Royal College Building, University of Strathclyde, Glasgow","institution_ids":["https://openalex.org/I181647926"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083586547","display_name":"Amlan Basu","orcid":"https://orcid.org/0000-0002-0180-8090","observed_orcids":["https://orcid.org/0000-0002-0180-8090"]},"institutions":[{"id":"https://openalex.org/I181647926","display_name":"University of Strathclyde","ror":"https://ror.org/00n3w3b69","country_code":"GB","type":"education","lineage":["https://openalex.org/I181647926"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Amlan Basu","raw_affiliation_strings":["CeSIP, Royal College Building, University of Strathclyde, Glasgow"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CeSIP, Royal College Building, University of Strathclyde, Glasgow","institution_ids":["https://openalex.org/I181647926"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017455396","display_name":"John J. Soraghan","orcid":"https://orcid.org/0000-0003-4418-7391","observed_orcids":["https://orcid.org/0000-0003-4418-7391"]},"institutions":[{"id":"https://openalex.org/I181647926","display_name":"University of Strathclyde","ror":"https://ror.org/00n3w3b69","country_code":"GB","type":"education","lineage":["https://openalex.org/I181647926"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"John Soraghan","raw_affiliation_strings":["CeSIP, Royal College Building, University of Strathclyde, Glasgow"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CeSIP, Royal College Building, University of Strathclyde, Glasgow","institution_ids":["https://openalex.org/I181647926"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009371598","display_name":"Gaetano Di Caterina","orcid":"https://orcid.org/0000-0002-7256-0897","observed_orcids":["https://orcid.org/0000-0002-7256-0897"]},"institutions":[{"id":"https://openalex.org/I181647926","display_name":"University of Strathclyde","ror":"https://ror.org/00n3w3b69","country_code":"GB","type":"education","lineage":["https://openalex.org/I181647926"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Gaetano Di Caterina","raw_affiliation_strings":["CeSIP, Royal College Building, University of Strathclyde, Glasgow"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CeSIP, Royal College Building, University of Strathclyde, Glasgow","institution_ids":["https://openalex.org/I181647926"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049987982","display_name":"Lykourgos Petropoulakis","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I181647926","display_name":"University of Strathclyde","ror":"https://ror.org/00n3w3b69","country_code":"GB","type":"education","lineage":["https://openalex.org/I181647926"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Lykourgos Petropoulakis","raw_affiliation_strings":["CeSIP, Royal College Building, University of Strathclyde, Glasgow"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CeSIP, Royal College Building, University of Strathclyde, Glasgow","institution_ids":["https://openalex.org/I181647926"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I181647926"],"apc_list":null,"apc_paid":null,"fwci":0.9788,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.81158063,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"374","last_page":"379"},"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/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":0.9994999766349792,"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/T10057","display_name":"Face and Expression Recognition","score":0.00019999999494757503,"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/T11448","display_name":"Face recognition and analysis","score":9.999999747378752e-05,"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/video-based-emotion-recognition","display_name":"video-based emotion recognition","score":0.8939999938011169},{"id":"https://openalex.org/keywords/facial-expression-recognition","display_name":"facial expression recognition","score":0.9670000076293945},{"id":"https://openalex.org/keywords/ravdess-dataset","display_name":"RAVDESS dataset","score":0.8679999709129333},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"emotion classification","score":0.6200000047683716},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.8349999785423279}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8250679969787598},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7358261346817017},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6766847968101501},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5607306957244873},{"id":"https://openalex.org/C65483669","wikidata":"https://www.wikidata.org/wiki/Q3536669","display_name":"Video processing","level":2,"score":0.5517331957817078},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.47273293137550354},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4710043966770172},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45129793882369995},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44228291511535645},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.43253758549690247},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.4322040379047394},{"id":"https://openalex.org/C2778598663","wikidata":"https://www.wikidata.org/wiki/Q1407599","display_name":"Video content analysis","level":4,"score":0.42182859778404236},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.418783038854599},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3988545536994934},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3891679048538208},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.3810933828353882},{"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},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3318299.3318321","doi":"https://doi.org/10.1145/3318299.3318321","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3318299.3318321","pdf_url":null,"source":{"id":"https://openalex.org/S7407088508","display_name":"International Conference on Machine Learning and Computing (ICMLC)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 11th International Conference on Machine Learning and Computing","raw_type":"proceedings-article"},{"id":"pmh:oai:strathprints.strath.ac.uk:65916","doi":null,"is_oa":false,"landing_page_url":"https://strathprints.strath.ac.uk/view/author/1042545.html>","pdf_url":null,"source":{"id":"https://openalex.org/S4306402226","display_name":"Strathprints: The University of Strathclyde institutional repository (University of Strathclyde)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I181647926","host_organization_name":"University of Strathclyde","host_organization_lineage":["https://openalex.org/I181647926"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Book Section"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1947481528","https://openalex.org/W2079735306","https://openalex.org/W2097117768","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2217896605","https://openalex.org/W2253728219","https://openalex.org/W2277498883","https://openalex.org/W2325078646","https://openalex.org/W2606933083","https://openalex.org/W2617750261","https://openalex.org/W2784263859","https://openalex.org/W2792191740","https://openalex.org/W2803193013","https://openalex.org/W2803347562","https://openalex.org/W2900454567","https://openalex.org/W2963875208","https://openalex.org/W4234552385"],"related_works":["https://openalex.org/W3201333618","https://openalex.org/W4249319343","https://openalex.org/W4386103310","https://openalex.org/W4393855296","https://openalex.org/W7166509224","https://openalex.org/W4211011512","https://openalex.org/W4285187935","https://openalex.org/W2281407413","https://openalex.org/W4210870303","https://openalex.org/W2547263832"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,98],"describe":[4],"a":[5,80,157,160,173],"new":[6,76,83,92,170,174,188],"image":[7],"pre-processing":[8,85,93,175],"method,":[9],"which":[10,104,196],"can":[11],"show":[12],"features":[13],"or":[14],"important":[15],"information":[16],"clearly.":[17],"Deep":[18,42],"learning":[19,37,43],"methods":[20,38],"have":[21,30],"grown":[22],"rapidly":[23],"in":[24,39,49,70,159,195],"the":[25,34,61,106,109,112,117,125,131,165,169,183,187,197],"last":[26],"ten":[27],"years":[28],"and":[29,66,72,86,123,180],"better":[31],"performance":[32],"than":[33],"traditional":[35],"machine":[36],"many":[40],"domains.":[41],"shows":[44],"its":[45],"powerful":[46],"ability":[47],"particular":[48],"difficult":[50],"multi-classes":[51],"classification":[52,64,184],"challenges.":[53],"Video":[54],"Facial":[55],"expression":[56],"recognition":[57,203],"is":[58,79,95,111,116],"one":[59],"of":[60,82,108,152,186],"most":[62],"popular":[63],"topics":[65],"will":[67],"become":[68],"essential":[69],"robotics":[71],"auto-motion":[73],"fields.":[74],"The":[75,91,144],"system":[77,171],"presented":[78],"combination":[81],"video":[84,118,132,141,146,155,167,201],"Convolutional":[87],"Neural":[88],"Network":[89],"(CNN).":[90],"method":[94,176,189],"proposed":[96],"because":[97],"believe":[99],"individual":[100],"emotions":[101],"are":[102,136],"dynamic,":[103],"means":[105],"change":[107],"face":[110],"key":[113],"feature.":[114],"RAVDESS":[115,129],"set":[119,147],"used,":[120],"to":[121],"train":[122],"test":[124],"neural":[126],"network.":[127],"From":[128],"dataset":[130,199],"songs":[133],"without":[134],"audio":[135],"taken":[137],"for":[138,200],"focusing":[139],"on":[140,164],"frames":[142],"differences.":[143],"chosen":[145,166],"has":[148,177,190],"six":[149],"different":[150],"classes":[151],"emotions.":[153],"Each":[154],"presents":[156],"sentence":[158],"melodious":[161],"way.":[162],"Based":[163],"set,":[168],"with":[172,193],"been":[178,191],"designed":[179],"trained.":[181],"Later,":[182],"result":[185],"compared":[192],"others":[194],"same":[198],"emotion":[202],"was":[204],"used.":[205]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2019-01-25T00:00:00"}