{"id":"https://openalex.org/W2907503465","doi":"https://doi.org/10.1109/tcsvt.2019.2890829","title":"Jointly Learning Visual Poses and Pose Lexicon for Semantic Action Recognition","display_name":"Jointly Learning Visual Poses and Pose Lexicon for Semantic Action Recognition","publication_year":2019,"publication_date":"2019-01-03","ids":{"openalex":"https://openalex.org/W2907503465","doi":"https://doi.org/10.1109/tcsvt.2019.2890829","mag":"2907503465"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2019.2890829","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2019.2890829","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/A5058467326","display_name":"Lijuan Zhou","orcid":"https://orcid.org/0000-0002-6418-6284"},"institutions":[{"id":"https://openalex.org/I204824540","display_name":"University of Wollongong","ror":"https://ror.org/00jtmb277","country_code":"AU","type":"education","lineage":["https://openalex.org/I204824540"]},{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["AU","CN"],"is_corresponding":false,"raw_author_name":"Lijuan Zhou","raw_affiliation_strings":["AMRL, University of Wollongong, Wollongong, Australia","Zhengzhou University, Zhengzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-6418-6284","affiliations":[{"raw_affiliation_string":"AMRL, University of Wollongong, Wollongong, Australia","institution_ids":["https://openalex.org/I204824540"]},{"raw_affiliation_string":"Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100695040","display_name":"Wanqing Li","orcid":"https://orcid.org/0000-0002-4427-2687"},"institutions":[{"id":"https://openalex.org/I204824540","display_name":"University of Wollongong","ror":"https://ror.org/00jtmb277","country_code":"AU","type":"education","lineage":["https://openalex.org/I204824540"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Wanqing Li","raw_affiliation_strings":["AMRL, University of Wollongong, Wollongong, Australia"],"raw_orcid":"https://orcid.org/0000-0002-4427-2687","affiliations":[{"raw_affiliation_string":"AMRL, University of Wollongong, Wollongong, Australia","institution_ids":["https://openalex.org/I204824540"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081319088","display_name":"Philip Ogunbona","orcid":"https://orcid.org/0000-0003-4119-2873"},"institutions":[{"id":"https://openalex.org/I204824540","display_name":"University of Wollongong","ror":"https://ror.org/00jtmb277","country_code":"AU","type":"education","lineage":["https://openalex.org/I204824540"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Philip Ogunbona","raw_affiliation_strings":["AMRL, University of Wollongong, Wollongong, Australia"],"raw_orcid":"https://orcid.org/0000-0003-4119-2873","affiliations":[{"raw_affiliation_string":"AMRL, University of Wollongong, Wollongong, Australia","institution_ids":["https://openalex.org/I204824540"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058849717","display_name":"Zhengyou Zhang","orcid":"https://orcid.org/0000-0002-6606-2525"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengyou Zhang","raw_affiliation_strings":["Microsoft Research, Redmond, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, Shenzhen, China","institution_ids":["https://openalex.org/I4210113369"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0169,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.80221078,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"30","issue":"2","first_page":"457","last_page":"467"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9962999820709229,"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":0.9937999844551086,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7845426797866821},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7754186391830444},{"id":"https://openalex.org/keywords/lexicon","display_name":"Lexicon","score":0.7692664861679077},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.6256375908851624},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.550329864025116},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46008041501045227},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4584694504737854},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4482281506061554}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7845426797866821},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7754186391830444},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.7692664861679077},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.6256375908851624},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.550329864025116},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46008041501045227},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4584694504737854},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4482281506061554},{"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:10.1109/tcsvt.2019.2890829","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2019.2890829","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"},{"id":"pmh:oai:ro.uow.edu.au:eispapers1-3290","is_oa":false,"landing_page_url":"https://ro.uow.edu.au/eispapers1/2283","pdf_url":null,"source":{"id":"https://openalex.org/S4306400510","display_name":"Research Online (University of Wollongong)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I204824540","host_organization_name":"University of Wollongong","host_organization_lineage":["https://openalex.org/I204824540"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Faculty of Engineering and Information Sciences - Papers: Part B","raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5699999928474426,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W129606432","https://openalex.org/W203345490","https://openalex.org/W225975350","https://openalex.org/W1441581489","https://openalex.org/W1880262756","https://openalex.org/W1942126453","https://openalex.org/W1967033562","https://openalex.org/W1995113806","https://openalex.org/W2001696967","https://openalex.org/W2006969979","https://openalex.org/W2020082763","https://openalex.org/W2038510448","https://openalex.org/W2038698865","https://openalex.org/W2047612595","https://openalex.org/W2064851185","https://openalex.org/W2089038880","https://openalex.org/W2096943734","https://openalex.org/W2125838338","https://openalex.org/W2130843763","https://openalex.org/W2134731454","https://openalex.org/W2137122906","https://openalex.org/W2139857301","https://openalex.org/W2140897751","https://openalex.org/W2142194269","https://openalex.org/W2142900973","https://openalex.org/W2144380653","https://openalex.org/W2145546283","https://openalex.org/W2158169396","https://openalex.org/W2258889121","https://openalex.org/W2296311849","https://openalex.org/W2296613712","https://openalex.org/W2304457967","https://openalex.org/W2315856743","https://openalex.org/W2344034899","https://openalex.org/W2554408731","https://openalex.org/W2726318948","https://openalex.org/W2727718475","https://openalex.org/W2736995747","https://openalex.org/W2759864339","https://openalex.org/W2895445581","https://openalex.org/W4239716185","https://openalex.org/W6605295763","https://openalex.org/W6628276711","https://openalex.org/W6639619044","https://openalex.org/W6652311901","https://openalex.org/W6680141653"],"related_works":["https://openalex.org/W2140536630","https://openalex.org/W3195005284","https://openalex.org/W2391730868","https://openalex.org/W2759814045","https://openalex.org/W2118055728","https://openalex.org/W2736760277","https://openalex.org/W4386940087","https://openalex.org/W4386931226","https://openalex.org/W4293870971","https://openalex.org/W1831473261"],"abstract_inverted_index":{"A":[0,17],"novel":[1],"method":[2,56,104,196],"for":[3],"semantic":[4,24,39,95,121,181],"action":[5,155,207],"recognition":[6],"through":[7],"learning":[8],"a":[9,21,26,32,55,60,80,127,138,148,160,169,177],"pose":[10,18,62,81,129,134,149,189],"lexicon":[11,19,82],"is":[12,135,144,157],"presented":[13],"in":[14],"this":[15],"paper.":[16],"comprises":[20],"set":[22,27],"of":[23,28,68,106,162,168,172,180],"poses,":[25,30,78,182],"visual":[29,37,47,61,77,91,118,128,133,188],"and":[31,38,49,53,79,93,120,131,190,205,213],"probabilistic":[33,86],"mapping":[34,50,87],"between":[35,88,116],"the":[36,46,66,85,89,94,102,114,117,152,164,185,191],"poses.":[40,122],"This":[41],"paper":[42],"assumes":[43],"that":[44,64,175],"both":[45],"poses":[48,92,96,119],"are":[51],"hidden":[52,76,90,108],"proposes":[54],"to":[57,146],"simultaneously":[58],"learn":[59],"model":[63,83],"estimates":[65],"likelihood":[67],"an":[69],"observed":[70],"video":[71,173],"frame":[72],"being":[73],"generated":[74],"from":[75,98],"establishes":[84],"parsed":[97],"textual":[99],"instructions.":[100],"Specifically,":[101],"proposed":[103,195],"consists":[105],"two-level":[107],"Markov":[109],"models.":[110],"One":[111],"level":[112,125],"represents":[113,126],"alignment":[115,192],"The":[123,194],"other":[124],"sequence,":[130],"each":[132],"modeled":[136],"as":[137,159],"Gaussian":[139],"mixture.":[140],"An":[141],"expectation-maximization":[142],"algorithm":[143],"developed":[145],"train":[147],"lexicon.":[150],"With":[151],"learned":[153],"lexicon,":[154],"classification":[156],"formulated":[158],"problem":[161],"finding":[163],"maximum":[165],"posterior":[166],"probability":[167],"given":[170,178],"sequence":[171,179],"frames":[174],"follows":[176],"constrained":[183],"by":[184],"most":[186],"likely":[187],"sequences.":[193],"was":[197],"evaluated":[198],"on":[199],"MSRC-12,":[200],"WorkoutSU-10,":[201],"WorkoutUOW-18,":[202],"Combined-15,":[203],"Combined-17,":[204],"Combined-50":[206],"datasets":[208],"using":[209],"cross-subject,":[210],"cross-dataset,":[211],"zero-shot,":[212],"seen/unseen":[214],"protocols.":[215]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}