{"id":"https://openalex.org/W3106564874","doi":"https://doi.org/10.1155/2020/8857748","title":"Capture of 3D Human Motion Pose in Virtual Reality Based on Video Recognition","display_name":"Capture of 3D Human Motion Pose in Virtual Reality Based on Video Recognition","publication_year":2020,"publication_date":"2020-11-20","ids":{"openalex":"https://openalex.org/W3106564874","doi":"https://doi.org/10.1155/2020/8857748","mag":"3106564874"},"language":"en","primary_location":{"id":"doi:10.1155/2020/8857748","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2020/8857748","pdf_url":"https://downloads.hindawi.com/journals/complexity/2020/8857748.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://downloads.hindawi.com/journals/complexity/2020/8857748.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002623953","display_name":"Qiang Fu","orcid":"https://orcid.org/0000-0001-6395-8521"},"institutions":[{"id":"https://openalex.org/I4210163247","display_name":"Henan Institute of Science and Technology","ror":"https://ror.org/0578f1k82","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163247"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Fu","raw_affiliation_strings":["Institute of Physical Culture, Henan Institute of Science and Technology, Xinxiang, Henan 453003, China"],"affiliations":[{"raw_affiliation_string":"Institute of Physical Culture, Henan Institute of Science and Technology, Xinxiang, Henan 453003, China","institution_ids":["https://openalex.org/I4210163247"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082567662","display_name":"Xingui Zhang","orcid":"https://orcid.org/0000-0001-5243-7683"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xingui Zhang","raw_affiliation_strings":["Department of Sports, Tsinghua University, Beijing 100084, China"],"affiliations":[{"raw_affiliation_string":"Department of Sports, Tsinghua University, Beijing 100084, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101095377","display_name":"Jinxiu Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I80626142","display_name":"Xinxiang Medical University","ror":"https://ror.org/038hzq450","country_code":"CN","type":"education","lineage":["https://openalex.org/I80626142"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinxiu Xu","raw_affiliation_strings":["Sanquan College of Xinxiang Medical University, Xinxiang, Henan 453003, China"],"affiliations":[{"raw_affiliation_string":"Sanquan College of Xinxiang Medical University, Xinxiang, Henan 453003, China","institution_ids":["https://openalex.org/I80626142"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067955677","display_name":"Haimin Zhang","orcid":"https://orcid.org/0000-0002-9386-7839"},"institutions":[{"id":"https://openalex.org/I4210163247","display_name":"Henan Institute of Science and Technology","ror":"https://ror.org/0578f1k82","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210163247"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haimin Zhang","raw_affiliation_strings":["Institute of Physical Culture, Henan Institute of Science and Technology, Xinxiang, Henan 453003, China"],"affiliations":[{"raw_affiliation_string":"Institute of Physical Culture, Henan Institute of Science and Technology, Xinxiang, Henan 453003, China","institution_ids":["https://openalex.org/I4210163247"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5082567662"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":{"value":2300,"currency":"USD","value_usd":2300},"apc_paid":{"value":2300,"currency":"USD","value_usd":2300},"fwci":0.4907,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.67052445,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"2020","issue":null,"first_page":"1","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9562000036239624,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9562000036239624,"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/T14413","display_name":"Advanced Technologies in Various Fields","score":0.9233999848365784,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7799054384231567},{"id":"https://openalex.org/keywords/motion-capture","display_name":"Motion capture","score":0.7475502490997314},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7339910268783569},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7090761661529541},{"id":"https://openalex.org/keywords/match-moving","display_name":"Match moving","score":0.5386673212051392},{"id":"https://openalex.org/keywords/virtual-reality","display_name":"Virtual reality","score":0.49350273609161377},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.47238850593566895},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.46411117911338806},{"id":"https://openalex.org/keywords/facial-motion-capture","display_name":"Facial motion capture","score":0.45624840259552},{"id":"https://openalex.org/keywords/motion-field","display_name":"Motion field","score":0.431990385055542},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.4179422855377197},{"id":"https://openalex.org/keywords/computer-animation","display_name":"Computer animation","score":0.4138537347316742},{"id":"https://openalex.org/keywords/gesture","display_name":"Gesture","score":0.4119790494441986},{"id":"https://openalex.org/keywords/animation","display_name":"Animation","score":0.39476680755615234},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.16634464263916016},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.1585129201412201},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.09229779243469238}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7799054384231567},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.7475502490997314},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7339910268783569},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7090761661529541},{"id":"https://openalex.org/C95020103","wikidata":"https://www.wikidata.org/wiki/Q1813492","display_name":"Match moving","level":3,"score":0.5386673212051392},{"id":"https://openalex.org/C194969405","wikidata":"https://www.wikidata.org/wiki/Q170519","display_name":"Virtual reality","level":2,"score":0.49350273609161377},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.47238850593566895},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.46411117911338806},{"id":"https://openalex.org/C98907195","wikidata":"https://www.wikidata.org/wiki/Q5428562","display_name":"Facial motion capture","level":5,"score":0.45624840259552},{"id":"https://openalex.org/C124774092","wikidata":"https://www.wikidata.org/wiki/Q6917782","display_name":"Motion field","level":3,"score":0.431990385055542},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.4179422855377197},{"id":"https://openalex.org/C69369342","wikidata":"https://www.wikidata.org/wiki/Q1401416","display_name":"Computer animation","level":3,"score":0.4138537347316742},{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.4119790494441986},{"id":"https://openalex.org/C502989409","wikidata":"https://www.wikidata.org/wiki/Q11425","display_name":"Animation","level":2,"score":0.39476680755615234},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.16634464263916016},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.1585129201412201},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.09229779243469238},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1155/2020/8857748","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2020/8857748","pdf_url":"https://downloads.hindawi.com/journals/complexity/2020/8857748.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:hin:complx:8857748","is_oa":false,"landing_page_url":"http://downloads.hindawi.com/journals/8503/2020/8857748.xml","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:doaj.org/article:c1c16e10d5394bf888bc7b79c3762355","is_oa":true,"landing_page_url":"https://doaj.org/article/c1c16e10d5394bf888bc7b79c3762355","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":"Complexity, Vol 2020 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2020/8857748","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2020/8857748","pdf_url":"https://downloads.hindawi.com/journals/complexity/2020/8857748.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3106564874.pdf","grobid_xml":"https://content.openalex.org/works/W3106564874.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W1612726527","https://openalex.org/W1970374087","https://openalex.org/W2042572748","https://openalex.org/W2044431436","https://openalex.org/W2160152944","https://openalex.org/W2256638885","https://openalex.org/W2296432816","https://openalex.org/W2404663615","https://openalex.org/W2568677893","https://openalex.org/W2594990926","https://openalex.org/W2608653446","https://openalex.org/W2609211977","https://openalex.org/W2743372195","https://openalex.org/W2779455887","https://openalex.org/W2783168053","https://openalex.org/W2792091145","https://openalex.org/W2800264158","https://openalex.org/W2805166665","https://openalex.org/W2810052972","https://openalex.org/W2818739605","https://openalex.org/W2892508882","https://openalex.org/W2893965229","https://openalex.org/W2895949813","https://openalex.org/W2912295676","https://openalex.org/W2947092242","https://openalex.org/W2950302183","https://openalex.org/W2955670944","https://openalex.org/W2963458581","https://openalex.org/W2964278319","https://openalex.org/W2967902380","https://openalex.org/W3003835452","https://openalex.org/W3005495055","https://openalex.org/W3018606973","https://openalex.org/W3021295796","https://openalex.org/W3031055318","https://openalex.org/W3042267487","https://openalex.org/W3103820901","https://openalex.org/W3104964198"],"related_works":["https://openalex.org/W2740961807","https://openalex.org/W585325435","https://openalex.org/W3196329781","https://openalex.org/W3169129874","https://openalex.org/W2089042722","https://openalex.org/W3040900128","https://openalex.org/W2358721113","https://openalex.org/W2070213417","https://openalex.org/W4214925816","https://openalex.org/W87457095"],"abstract_inverted_index":{"Motion":[0,44],"pose":[1,223],"capture":[2,46,200,217,240,297,355],"technology":[3,47],"can":[4,226],"effectively":[5],"solve":[6],"the":[7,16,25,33,39,62,92,96,104,127,132,139,143,148,152,158,163,166,170,185,190,196,216,221,229,249,256,260,268,289,292,310,318,325,333,348],"problem":[8],"of":[9,18,27,35,41,61,65,95,126,134,142,151,157,165,172,236,263,270,291,307,312,320,345],"difficulty":[10],"in":[11,15,51,189],"defining":[12],"character":[13,28,42],"motion":[14,29,63,140,167,174,198,208,238,261,265,272,295,353],"process":[17,262],"3D":[19],"animation":[20,36],"production":[21],"and":[22,38,58,122,145,215,243,246,280,298,332,356],"greatly":[23],"reduce":[24],"workload":[26],"control,":[30],"thereby":[31],"improving":[32],"efficiency":[34],"development":[37],"fidelity":[40],"motion.":[43,232],"gesture":[45,209,296,354],"is":[48,84,116,160,210,315,328,338,358],"widely":[49],"used":[50,130],"virtual":[52,55],"reality":[53],"systems,":[54],"training":[56],"grounds,":[57],"real-time":[59],"tracking":[60],"trajectories":[64],"general":[66],"objects.":[67],"This":[68],"paper":[69,178,275],"proposes":[70],"an":[71],"attitude":[72],"estimation":[73],"algorithm":[74],"adapted":[75],"to":[76,91,102,137,162],"be":[77],"embedded.":[78],"The":[79,118,154,192,205,304],"previous":[80],"centralized":[81],"Kalman":[82,88],"filter":[83],"divided":[85],"into":[86],"two-step":[87],"filtering.":[89],"According":[90],"different":[93],"characteristics":[94],"sensors,":[97],"they":[98],"are":[99,129],"processed":[100],"separately":[101],"isolate":[103],"cross-influence":[105],"between":[106],"sensors.":[107],"An":[108],"adaptive":[109,155],"adjustment":[110,156],"method":[111,201],"based":[112,183],"on":[113,184,309],"fuzzy":[114,135],"logic":[115,136],"proposed.":[117],"acceleration,":[119],"angular":[120],"velocity,":[121],"geomagnetic":[123],"field":[124],"strength":[125],"environment":[128],"as":[131],"input":[133],"judge":[138],"state":[141],"carrier":[144],"then":[146],"adjust":[147],"covariance":[149],"matrix":[150],"filter.":[153],"sensor":[159],"converted":[161],"recognition":[164,299,311,335,346,357],"state.":[168],"For":[169,267],"study":[171],"human":[173,206,230,237,264,271,281,294,352],"posture":[175,199,239],"capture,":[176],"this":[177,274],"designs":[179,276],"a":[180,277],"verification":[181],"experiment":[182,193],"existing":[186],"robotic":[187],"arm":[188],"laboratory.":[191],"shows":[194],"that":[195,220,255,288],"studied":[197],"has":[202,300],"better":[203,227],"performance.":[204],"body":[207,231],"designed":[211],"for":[212,284,351],"capturing":[213],"experiments,":[214],"results":[218],"show":[219,287],"obtained":[222],"angle":[224],"information":[225],"restore":[228],"A":[233],"visual":[234],"model":[235,279],"was":[241,253],"established,":[242],"after":[244],"comparing":[245],"analyzing":[247],"with":[248],"real":[250],"situation,":[251],"it":[252],"found":[254],"simulation":[257],"approach":[258],"reproduced":[259],"well.":[266],"research":[269],"recognition,":[273],"two-classification":[278],"daily":[282],"behaviors":[283],"experiments.":[285],"Experiments":[286],"accuracy":[290,326,336],"two-category":[293],"achieved":[301],"good":[302],"results.":[303],"experimental":[305],"effect":[306],"SVC":[308],"two":[313],"classifications":[314],"excellent.":[316],"In":[317,343],"case":[319],"using":[321],"all":[322],"optimization":[323],"algorithms,":[324],"rate":[327,337],"higher":[329,340],"than":[330,341,360],"90%,":[331],"final":[334],"also":[339],"90%.":[342],"terms":[344],"time,":[347],"time":[349],"required":[350],"less":[359],"2":[361],"s.":[362]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}