{"id":"https://openalex.org/W2984349976","doi":"https://doi.org/10.1109/tcsvt.2019.2953678","title":"Multi-Person Hierarchical 3D Pose Estimation in Natural Videos","display_name":"Multi-Person Hierarchical 3D Pose Estimation in Natural Videos","publication_year":2019,"publication_date":"2019-11-15","ids":{"openalex":"https://openalex.org/W2984349976","doi":"https://doi.org/10.1109/tcsvt.2019.2953678","mag":"2984349976"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2019.2953678","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2019.2953678","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Circuits and Systems for Video Technology","raw_type":"journal-article"},"type":"article","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/A5045766331","display_name":"Renshu Gu","orcid":"https://orcid.org/0000-0002-3900-2148"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Renshu Gu","raw_affiliation_strings":["Electrical and Computer Engineering, University of Washington, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089410490","display_name":"Gaoang Wang","orcid":"https://orcid.org/0000-0002-8403-1538"},"institutions":[{"id":"https://openalex.org/I24571045","display_name":"University of North Dakota","ror":"https://ror.org/04a5szx83","country_code":"US","type":"education","lineage":["https://openalex.org/I24571045"]},{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gaoang Wang","raw_affiliation_strings":["University of Washington, Forks, WA, USA"],"affiliations":[{"raw_affiliation_string":"University of Washington, Forks, WA, USA","institution_ids":["https://openalex.org/I24571045","https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101618974","display_name":"Zhongyu Jiang","orcid":"https://orcid.org/0000-0003-4462-6497"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]},{"id":"https://openalex.org/I24571045","display_name":"University of North Dakota","ror":"https://ror.org/04a5szx83","country_code":"US","type":"education","lineage":["https://openalex.org/I24571045"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhongyu Jiang","raw_affiliation_strings":["University of Washington, Forks, WA, USA"],"affiliations":[{"raw_affiliation_string":"University of Washington, Forks, WA, USA","institution_ids":["https://openalex.org/I24571045","https://openalex.org/I201448701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101702810","display_name":"Jenq\u2013Neng Hwang","orcid":"https://orcid.org/0000-0002-8877-2421"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jenq-Neng Hwang","raw_affiliation_strings":["Electrical and Computer Engineering, University of Washington, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Electrical and Computer Engineering, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5045766331"],"corresponding_institution_ids":["https://openalex.org/I201448701"],"apc_list":null,"apc_paid":null,"fwci":3.0367,"has_fulltext":false,"cited_by_count":69,"citation_normalized_percentile":{"value":0.93431835,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"30","issue":"11","first_page":"4245","last_page":"4257"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994000196456909,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9947999715805054,"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/pose","display_name":"Pose","score":0.8929928541183472},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7696961164474487},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.7341068983078003},{"id":"https://openalex.org/keywords/torso","display_name":"Torso","score":0.7109848856925964},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.698046088218689},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.673204243183136},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.5129132270812988},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.5097770094871521},{"id":"https://openalex.org/keywords/articulated-body-pose-estimation","display_name":"Articulated body pose estimation","score":0.4734218716621399},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4687122702598572},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.4470585584640503},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37960925698280334},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.10960736870765686},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07878696918487549}],"concepts":[{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.8929928541183472},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7696961164474487},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.7341068983078003},{"id":"https://openalex.org/C523889960","wikidata":"https://www.wikidata.org/wiki/Q160695","display_name":"Torso","level":2,"score":0.7109848856925964},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.698046088218689},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.673204243183136},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.5129132270812988},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.5097770094871521},{"id":"https://openalex.org/C22100474","wikidata":"https://www.wikidata.org/wiki/Q4800952","display_name":"Articulated body pose estimation","level":4,"score":0.4734218716621399},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4687122702598572},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.4470585584640503},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37960925698280334},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.10960736870765686},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07878696918487549},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C105702510","wikidata":"https://www.wikidata.org/wiki/Q514","display_name":"Anatomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsvt.2019.2953678","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2019.2953678","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Circuits and Systems for Video Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5600000023841858,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1510906150","https://openalex.org/W1565886950","https://openalex.org/W1643263348","https://openalex.org/W1905368000","https://openalex.org/W1930799357","https://openalex.org/W1943191679","https://openalex.org/W1948369226","https://openalex.org/W1996478295","https://openalex.org/W2039262381","https://openalex.org/W2046554054","https://openalex.org/W2074138208","https://openalex.org/W2080873731","https://openalex.org/W2088196373","https://openalex.org/W2097649661","https://openalex.org/W2101032778","https://openalex.org/W2111446867","https://openalex.org/W2113325037","https://openalex.org/W2114013702","https://openalex.org/W2115579991","https://openalex.org/W2123503110","https://openalex.org/W2136391815","https://openalex.org/W2150183285","https://openalex.org/W2155196764","https://openalex.org/W2155394491","https://openalex.org/W2256477790","https://openalex.org/W2293220651","https://openalex.org/W2307770531","https://openalex.org/W2337500368","https://openalex.org/W2483862638","https://openalex.org/W2518965973","https://openalex.org/W2554247908","https://openalex.org/W2559085405","https://openalex.org/W2564632156","https://openalex.org/W2605947573","https://openalex.org/W2619649711","https://openalex.org/W2756050327","https://openalex.org/W2774615707","https://openalex.org/W2781181706","https://openalex.org/W2792747672","https://openalex.org/W2799870331","https://openalex.org/W2894950214","https://openalex.org/W2922507888","https://openalex.org/W2952422028","https://openalex.org/W2963013806","https://openalex.org/W2963738870","https://openalex.org/W2964105113","https://openalex.org/W2964297864","https://openalex.org/W2964304707","https://openalex.org/W2981648413","https://openalex.org/W6640740087","https://openalex.org/W6680285999","https://openalex.org/W6682891246","https://openalex.org/W6696920397","https://openalex.org/W6712333017","https://openalex.org/W6738540877"],"related_works":["https://openalex.org/W2946083937","https://openalex.org/W2798721181","https://openalex.org/W2951583186","https://openalex.org/W4299867837","https://openalex.org/W2088028039","https://openalex.org/W4382141741","https://openalex.org/W4386075737","https://openalex.org/W1968783203","https://openalex.org/W4206633503","https://openalex.org/W2574567538"],"abstract_inverted_index":{"Despite":[0],"the":[1,9,13,42,73,101,108],"increasing":[2],"need":[3,74],"of":[4,45,75,117],"analyzing":[5],"human":[6,49,63,130,147],"poses":[7,64,104],"on":[8,122],"street":[10,126],"and":[11,59,90,98,114,128,135,145],"in":[12,25,47,65,68,139],"wild,":[14],"multi-person":[15,118],"3D":[16,48,62,78,119],"pose":[17,92,120],"estimation":[18,84,93,121],"using":[19,76],"monocular":[20],"static":[21],"or":[22,36],"moving":[23,136],"camera":[24],"real-world":[26,123],"scenarios":[27,127],"remains":[28],"a":[29,53,86],"challenge,":[30],"either":[31],"requiring":[32],"large-scale":[33],"training":[34,79],"data":[35],"high":[37,43,102,115],"computation":[38],"complexity":[39],"due":[40],"to":[41,56,105,143],"degrees":[44],"freedom":[46],"poses.":[50],"We":[51],"propose":[52],"novel":[54],"scheme":[55],"effectively":[57],"track":[58],"hierarchically":[60,99],"estimate":[61],"natural":[66],"videos":[67],"an":[69,95],"efficient":[70],"fashion.":[71],"Without":[72],"labelled":[77],"data,":[80],"we":[81],"formulate":[82],"torso":[83],"as":[85,94],"Perspective-N-Point":[87],"(PNP)":[88],"problem,":[89,97],"limb":[91],"optimization":[96],"structure":[100],"dimensional":[103],"efficiently":[106],"address":[107],"challenge.":[109],"Experiments":[110],"show":[111],"good":[112],"performance":[113],"efficiency":[116],"videos,":[124],"including":[125],"various":[129],"daily":[131],"activities":[132],"from":[133],"fixed":[134],"cameras,":[137],"resulting":[138],"great":[140],"new":[141],"opportunities":[142],"understand":[144],"predict":[146],"behaviors.":[148]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":26},{"year":2022,"cited_by_count":27},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}