{"id":"https://openalex.org/W2892046417","doi":"https://doi.org/10.1109/access.2018.2868319","title":"Human Action Recognition Based on Integrating Body Pose, Part Shape, and Motion","display_name":"Human Action Recognition Based on Integrating Body Pose, Part Shape, and Motion","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2892046417","doi":"https://doi.org/10.1109/access.2018.2868319","mag":"2892046417"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2868319","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2868319","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,"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":null,"license_id":null,"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://doi.org/10.1109/access.2018.2868319","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043913668","display_name":"Hany El-Ghaish","orcid":"https://orcid.org/0000-0003-4182-0016"},"institutions":[{"id":"https://openalex.org/I32619867","display_name":"Egypt-Japan University of Science and Technology","ror":"https://ror.org/02x66tk73","country_code":"EG","type":"education","lineage":["https://openalex.org/I32619867"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Hany El-Ghaish","raw_affiliation_strings":["Department of Computer Science and Engineering, Egypt-Japan University of Science and Technology, New Borg El-Arab City, Alexandria, Egypt"],"raw_orcid":"https://orcid.org/0000-0003-4182-0016","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Egypt-Japan University of Science and Technology, New Borg El-Arab City, Alexandria, Egypt","institution_ids":["https://openalex.org/I32619867"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111492379","display_name":"Mohamed E. Hussien","orcid":null},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohamed E. Hussien","raw_affiliation_strings":["University of Southern California, Los Angeles, CA, US"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Southern California, Los Angeles, CA, US","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048030732","display_name":"Amin Shoukry","orcid":"https://orcid.org/0000-0002-8024-3795"},"institutions":[{"id":"https://openalex.org/I32619867","display_name":"Egypt-Japan University of Science and Technology","ror":"https://ror.org/02x66tk73","country_code":"EG","type":"education","lineage":["https://openalex.org/I32619867"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Amin Shoukry","raw_affiliation_strings":["Department of Computer Science and Engineering, Egypt-Japan University of Science and Technology, New Borg El-Arab City, Alexandria, Egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Egypt-Japan University of Science and Technology, New Borg El-Arab City, Alexandria, Egypt","institution_ids":["https://openalex.org/I32619867"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081288271","display_name":"Rikio Onai","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Rikio Onai","raw_affiliation_strings":["Department of Computer Science and Engineering, Waseda University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Waseda University, Tokyo, Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.166,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.84069881,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"6","issue":null,"first_page":"49040","last_page":"49055"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":1.0,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9976000189781189,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7890048623085022},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7576723098754883},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.5881001949310303},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5878950357437134},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5569370985031128},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.550069272518158},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5376042127609253},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5236839056015015},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.5211881995201111},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.5087140202522278},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4828084707260132},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.45250073075294495},{"id":"https://openalex.org/keywords/motion-capture","display_name":"Motion capture","score":0.42299288511276245},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4220905005931854},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.34348922967910767}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7890048623085022},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7576723098754883},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.5881001949310303},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5878950357437134},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5569370985031128},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.550069272518158},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5376042127609253},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5236839056015015},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.5211881995201111},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.5087140202522278},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4828084707260132},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.45250073075294495},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.42299288511276245},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4220905005931854},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34348922967910767},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2868319","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2868319","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,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:713ae66707a6456f9744bc0fff2ada98","is_oa":true,"landing_page_url":"https://doaj.org/article/713ae66707a6456f9744bc0fff2ada98","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,"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 6, Pp 49040-49055 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2868319","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2868319","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,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.49000000953674316,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":89,"referenced_works":["https://openalex.org/W28988658","https://openalex.org/W146508469","https://openalex.org/W203345490","https://openalex.org/W796858280","https://openalex.org/W1522301498","https://openalex.org/W1536929369","https://openalex.org/W1538131130","https://openalex.org/W1621899174","https://openalex.org/W1744759976","https://openalex.org/W1810943226","https://openalex.org/W1883922301","https://openalex.org/W1893516992","https://openalex.org/W1950788856","https://openalex.org/W1969117674","https://openalex.org/W1985912834","https://openalex.org/W1995113806","https://openalex.org/W2000059041","https://openalex.org/W2007057255","https://openalex.org/W2008765809","https://openalex.org/W2021150171","https://openalex.org/W2048821851","https://openalex.org/W2052648922","https://openalex.org/W2058256495","https://openalex.org/W2062227835","https://openalex.org/W2085735683","https://openalex.org/W2087461551","https://openalex.org/W2091911422","https://openalex.org/W2145546283","https://openalex.org/W2149645715","https://openalex.org/W2153472500","https://openalex.org/W2163605009","https://openalex.org/W2183341477","https://openalex.org/W2230000137","https://openalex.org/W2295038166","https://openalex.org/W2344034899","https://openalex.org/W2441438155","https://openalex.org/W2475271590","https://openalex.org/W2510185399","https://openalex.org/W2556782416","https://openalex.org/W2593146028","https://openalex.org/W2602311553","https://openalex.org/W2603861860","https://openalex.org/W2604321021","https://openalex.org/W2612707971","https://openalex.org/W2735590100","https://openalex.org/W2736334449","https://openalex.org/W2751555739","https://openalex.org/W2751841288","https://openalex.org/W2761860076","https://openalex.org/W2777646139","https://openalex.org/W2793450605","https://openalex.org/W2892409420","https://openalex.org/W2950568498","https://openalex.org/W2952587893","https://openalex.org/W2963032654","https://openalex.org/W2963192057","https://openalex.org/W2964134613","https://openalex.org/W3098538019","https://openalex.org/W3099037876","https://openalex.org/W3103858256","https://openalex.org/W4240042586","https://openalex.org/W6601175079","https://openalex.org/W6605964401","https://openalex.org/W6608276133","https://openalex.org/W6622994109","https://openalex.org/W6632100814","https://openalex.org/W6636478268","https://openalex.org/W6639383027","https://openalex.org/W6639400878","https://openalex.org/W6640754710","https://openalex.org/W6650576099","https://openalex.org/W6662688328","https://openalex.org/W6664918956","https://openalex.org/W6671914997","https://openalex.org/W6673530336","https://openalex.org/W6684191040","https://openalex.org/W6686164453","https://openalex.org/W6689569396","https://openalex.org/W6698200468","https://openalex.org/W6704520437","https://openalex.org/W6718545058","https://openalex.org/W6721026953","https://openalex.org/W6725062358","https://openalex.org/W6730028046","https://openalex.org/W6737019326","https://openalex.org/W6737954372","https://openalex.org/W6740961951","https://openalex.org/W6743852643","https://openalex.org/W6746593864"],"related_works":["https://openalex.org/W2385859805","https://openalex.org/W2530972254","https://openalex.org/W2374013449","https://openalex.org/W73545470","https://openalex.org/W2364381299","https://openalex.org/W2901551566","https://openalex.org/W4303411729","https://openalex.org/W2004108207","https://openalex.org/W2965803933","https://openalex.org/W4211202157"],"abstract_inverted_index":{"Human":[0],"action":[1,46],"recognition":[2,230],"is":[3,93,130],"a":[4,39,121,126,184],"challenging":[5],"problem,":[6],"especially":[7],"in":[8,14,171],"the":[9,15,52,66,71,78,81,87,94,99,103,166,172,233,238],"presence":[10],"of":[11,55,80,89,145,177],"multiple":[12],"actors":[13],"scene":[16],"and/or":[17],"viewpoint":[18],"variations.":[19],"In":[20],"this":[21],"paper,":[22],"three":[23,49,146,173,179],"modalities,":[24],"namely,":[25],"3-D":[26,67],"skeletons,":[27],"body":[28,58,63,82],"part":[29,60],"images,":[30],"and":[31,62,102,120,158,168,205,213,226],"motion":[32],"history":[33],"image":[34],"(MHI),":[35],"are":[36,181],"integrated":[37],"into":[38,125],"hybrid":[40,127],"deep":[41],"learning":[42],"architecture":[43,110,124],"for":[44,96,161],"human":[45],"recognition.":[47],"The":[48,108,142,175,201],"modalities":[50],"capture":[51],"main":[53],"aspects":[54],"an":[56],"action:":[57],"pose,":[59,73],"shape,":[61],"motion.":[64],"Although":[65],"skeleton":[68],"modality":[69],"captures":[70],"actor's":[72],"it":[74],"lacks":[75],"information":[76],"about":[77],"shape":[79,88],"parts":[83],"as":[84,86,105],"well":[85],"manipulated":[90],"objects.":[91],"This":[92],"reason":[95],"including":[97],"both":[98,211],"body-part":[100],"images":[101],"MHI":[104],"additional":[106],"modalities.":[107,174],"deployed":[109],"combines":[111],"convolution":[112],"neural":[113],"networks":[114],"(CNNs),":[115],"long":[116],"short-term":[117],"memory":[118],"(LSTM),":[119],"fine-tuned":[122],"pre-trained":[123,139],"one.":[128],"It":[129],"called":[131],"MCLP:":[132],"multi-modal":[133],"CNN":[134],"+":[135,137,151,156],"LSTM":[136],"VGG16":[138],"on":[140,215,236],"ImageNet.":[141],"MCLP":[143],"consists":[144],"sub-models:":[147],"CL1D":[148],"(for":[149,154],"CNN1D":[150],"LSTM),":[152,157],"CL2D":[153],"CNN2D":[155],"CMHI":[159],"(CNN2D":[160],"MHI),":[162],"which":[163,189],"simultaneously":[164],"extract":[165],"spatial":[167],"temporal":[169],"patterns":[170],"decisions":[176],"these":[178],"sub-models":[180],"fused":[182],"by":[183],"late":[185],"multiply":[186],"fusion":[187,199],"module,":[188],"proved":[190],"to":[191],"yield":[192],"better":[193],"accuracy":[194],"than":[195],"averaging":[196],"or":[197],"maximizing":[198],"methods.":[200],"proposed":[202],"combined":[203],"model":[204],"its":[206],"submodels":[207],"have":[208],"been":[209],"evaluated":[210,239],"individually":[212],"collectively":[214],"four":[216],"public":[217],"data":[218,240],"sets:":[219],"UTkinect":[220],"Action3D,":[221],"SBU":[222],"Interaction,":[223],"Florence3-D":[224],"Action,":[225],"NTU":[227],"RGB+D.":[228],"Our":[229],"rates":[231,235],"outperform":[232],"state-ofthe-art":[234],"all":[237],"sets.":[241]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
