{"id":"https://openalex.org/W3159380009","doi":"https://doi.org/10.1109/healthcom49281.2021.9399007","title":"Multi-Level Co-Occurrence Graph Convolutional LSTM for Skeleton-Based Action Recognition","display_name":"Multi-Level Co-Occurrence Graph Convolutional LSTM for Skeleton-Based Action Recognition","publication_year":2021,"publication_date":"2021-03-01","ids":{"openalex":"https://openalex.org/W3159380009","doi":"https://doi.org/10.1109/healthcom49281.2021.9399007","mag":"3159380009"},"language":"en","primary_location":{"id":"doi:10.1109/healthcom49281.2021.9399007","is_oa":false,"landing_page_url":"https://doi.org/10.1109/healthcom49281.2021.9399007","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on E-health Networking, Application & Services (HEALTHCOM)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5037441265","display_name":"Shihao Xu","orcid":"https://orcid.org/0000-0002-1522-730X"},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shihao Xu","raw_affiliation_strings":["Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China","institution_ids":["https://openalex.org/I4210145761"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020629462","display_name":"Haocong Rao","orcid":"https://orcid.org/0000-0002-9576-2379"},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haocong Rao","raw_affiliation_strings":["Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China","institution_ids":["https://openalex.org/I4210145761"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007941489","display_name":"Xiping Hu","orcid":"https://orcid.org/0000-0002-4952-699X"},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiping Hu","raw_affiliation_strings":["Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China","institution_ids":["https://openalex.org/I4210145761"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100380066","display_name":"Bin Hu","orcid":"https://orcid.org/0000-0003-3514-5413"},"institutions":[{"id":"https://openalex.org/I76214153","display_name":"Lanzhou University","ror":"https://ror.org/01mkqqe32","country_code":"CN","type":"education","lineage":["https://openalex.org/I76214153"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Hu","raw_affiliation_strings":["Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China","institution_ids":["https://openalex.org/I76214153"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"abs 1609 2907","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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":0.9998999834060669,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9871000051498413,"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"}},{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9779999852180481,"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":0.8399378061294556},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6156623363494873},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5947459936141968},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5749703049659729},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5605129599571228},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5087001919746399},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5077072381973267},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4622340798377991},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38764166831970215},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.11484658718109131}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8399378061294556},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6156623363494873},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5947459936141968},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5749703049659729},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5605129599571228},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5087001919746399},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5077072381973267},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4622340798377991},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38764166831970215},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.11484658718109131},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/healthcom49281.2021.9399007","is_oa":false,"landing_page_url":"https://doi.org/10.1109/healthcom49281.2021.9399007","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on E-health Networking, Application & Services (HEALTHCOM)","raw_type":"proceedings-article"},{"id":"pmh:oai:ir.lzu.edu.cn/:262010/451335","is_oa":false,"landing_page_url":"http://ir.lzu.edu.cn/handle/262010/451335","pdf_url":null,"source":{"id":"https://openalex.org/S4406923049","display_name":"Lanzhou University Institutional Repository","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference article (CA)"},{"id":"pmh:oai:ir.lzu.edu.cn/:262010/451462","is_oa":false,"landing_page_url":"http://ir.lzu.edu.cn/handle/262010/451462","pdf_url":null,"source":{"id":"https://openalex.org/S4406923049","display_name":"Lanzhou University Institutional Repository","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"\u4f1a\u8bae\u8bba\u6587"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G4545754438","display_name":null,"funder_award_id":"Z171100000117005","funder_id":"https://openalex.org/F4320325902","funder_display_name":"Beijing Municipal Science and Technology Commission"},{"id":"https://openalex.org/G5073799558","display_name":null,"funder_award_id":"2014CB744600","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5197980865","display_name":null,"funder_award_id":"2019YFA0706200","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5828742806","display_name":null,"funder_award_id":"61632014,61627808,61210010","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320325902","display_name":"Beijing Municipal Science and Technology Commission","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":81,"referenced_works":["https://openalex.org/W101951079","https://openalex.org/W203345490","https://openalex.org/W1446523894","https://openalex.org/W1522301498","https://openalex.org/W1662382123","https://openalex.org/W1893516992","https://openalex.org/W1983705368","https://openalex.org/W1984219317","https://openalex.org/W1989912492","https://openalex.org/W2048821851","https://openalex.org/W2054041160","https://openalex.org/W2056898157","https://openalex.org/W2064675550","https://openalex.org/W2090834590","https://openalex.org/W2101491865","https://openalex.org/W2110819057","https://openalex.org/W2143267104","https://openalex.org/W2169852119","https://openalex.org/W2224196924","https://openalex.org/W2313903725","https://openalex.org/W2399415452","https://openalex.org/W2510185399","https://openalex.org/W2556782416","https://openalex.org/W2558460151","https://openalex.org/W2559085405","https://openalex.org/W2593146028","https://openalex.org/W2604321021","https://openalex.org/W2716916105","https://openalex.org/W2736334449","https://openalex.org/W2793547936","https://openalex.org/W2798644314","https://openalex.org/W2799211965","https://openalex.org/W2885940446","https://openalex.org/W2890531016","https://openalex.org/W2914177721","https://openalex.org/W2944006115","https://openalex.org/W2944017438","https://openalex.org/W2948058585","https://openalex.org/W2950568498","https://openalex.org/W2952587893","https://openalex.org/W2956928039","https://openalex.org/W2962767366","https://openalex.org/W2963076818","https://openalex.org/W2963241486","https://openalex.org/W2963369114","https://openalex.org/W2964015378","https://openalex.org/W2964113829","https://openalex.org/W2964121744","https://openalex.org/W2964134613","https://openalex.org/W2964145825","https://openalex.org/W2964311892","https://openalex.org/W2964321699","https://openalex.org/W2966438217","https://openalex.org/W2982542880","https://openalex.org/W3035050855","https://openalex.org/W3035225512","https://openalex.org/W3098538019","https://openalex.org/W3123784868","https://openalex.org/W4230005465","https://openalex.org/W4294558607","https://openalex.org/W4300650665","https://openalex.org/W6604185612","https://openalex.org/W6608276133","https://openalex.org/W6628555714","https://openalex.org/W6631190155","https://openalex.org/W6637178625","https://openalex.org/W6646495098","https://openalex.org/W6672997307","https://openalex.org/W6675374677","https://openalex.org/W6685350579","https://openalex.org/W6698200468","https://openalex.org/W6713582119","https://openalex.org/W6720006811","https://openalex.org/W6725062358","https://openalex.org/W6726873649","https://openalex.org/W6738964360","https://openalex.org/W6746580039","https://openalex.org/W6753525637","https://openalex.org/W6754778999","https://openalex.org/W6758943949","https://openalex.org/W6789831707"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W4239306820","https://openalex.org/W2947043951","https://openalex.org/W2787993192","https://openalex.org/W4285218279"],"abstract_inverted_index":{"Human":[0],"action":[1,23,57,176,192],"recognition":[2,24],"plays":[3],"an":[4,30],"important":[5],"role":[6],"in":[7],"e-health":[8],"applications,":[9],"such":[10],"as":[11],"surgical":[12],"skill":[13],"analysis,":[14],"patient":[15],"monitoring,":[16],"and":[17,43,146,156,179,209],"automatic":[18],"nursing":[19],"systems.":[20],"Recently,":[21],"skeleton-based":[22],"gains":[25],"massive":[26],"attention.":[27],"It":[28],"is":[29],"essential":[31],"yet":[32,63],"challenging":[33],"task":[34],"that":[35,196],"requires":[36],"effectively":[37],"modeling":[38],"the":[39,68,121,141,149,174],"intra-frame":[40,175],"skeleton":[41],"representation":[42],"inter-frame":[44],"temporal":[45,189],"dynamics.":[46],"Traditional":[47],"Long":[48],"Short-Term":[49],"Memory":[50],"(LSTM)":[51],"based":[52],"methods":[53,203],"mainly":[54],"capture":[55,148],"long-term":[56],"context":[58,177],"information":[59,115],"from":[60,80,116,152,167],"global":[61],"level,":[62],"they":[64],"cannot":[65],"fully":[66],"model":[67,107,140,187,199],"relationship":[69,143],"between":[70,144],"different":[71,81,153],"joints":[72],"or":[73],"persons":[74],"to":[75,138,171,185],"mine":[76],"crucial":[77],"co-occurrence":[78,123,131,150],"features":[79,151,162],"levels.":[82],"To":[83],"overcome":[84],"this":[85],"drawback,":[86],"we":[87,127,159],"propose":[88],"a":[89,181],"general":[90],"end-to-end":[91],"Multi-level":[92],"Co-occurrence":[93],"Graph":[94],"Convolutional":[95],"LSTM":[96,183],"(MCGC-LSTM).":[97],"By":[98],"incorporating":[99],"graph":[100],"convolutional":[101],"networks":[102],"(GCN)":[103],"into":[104],"LSTM,":[105],"our":[106,197],"can":[108],"not":[109],"only":[110],"better":[111,172],"exploit":[112],"body":[113],"structural":[114],"skeletons":[117],"but":[118],"also":[119],"enhance":[120],"multi-level":[122,130,164],"feature":[124],"learning.":[125],"Specifically,":[126],"first":[128],"devise":[129],"(MC)":[132],"memory":[133,169],"units":[134,170],"coupled":[135],"with":[136],"GCN":[137],"automatically":[139],"spatial":[142],"joints,":[145,154],"simultaneously":[147],"persons,":[155],"frames.":[157],"Then":[158],"construct":[160],"aggregated":[161],"of":[163],"co-occurrences":[165],"(AFMC)":[166],"MC":[168],"represent":[173],"encoding,":[178],"leverage":[180],"concurrent":[182],"(Co-LSTM)":[184],"further":[186],"their":[188],"dynamics":[190],"for":[191],"recognition.":[193],"Experiments":[194],"show":[195],"proposed":[198],"significantly":[200],"outperforms":[201],"mainstream":[202],"on":[204],"NTU":[205],"RGB+D":[206],"120":[207],"dataset":[208],"Northwestern-UCLA":[210],"dataset.":[211]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}