{"id":"https://openalex.org/W2609674290","doi":"https://doi.org/10.1109/icpr.2016.7900051","title":"Depth-based 3D hand pose tracking","display_name":"Depth-based 3D hand pose tracking","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2609674290","doi":"https://doi.org/10.1109/icpr.2016.7900051","mag":"2609674290"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2016.7900051","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7900051","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-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/A5023840296","display_name":"Kha Gia Quach","orcid":"https://orcid.org/0000-0001-6952-306X"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Kha Gia Quach","raw_affiliation_strings":["Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007006341","display_name":"Chi Nhan Duong","orcid":"https://orcid.org/0000-0002-5177-0393"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Chi Nhan Duong","raw_affiliation_strings":["Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056226189","display_name":"Khoa Luu","orcid":"https://orcid.org/0000-0003-2104-0901"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Khoa Luu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101511820","display_name":"Tien D. Bui","orcid":"https://orcid.org/0000-0001-6005-4375"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Tien D. Bui","raw_affiliation_strings":["Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec, Canada","institution_ids":["https://openalex.org/I60158472"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5023840296"],"corresponding_institution_ids":["https://openalex.org/I60158472"],"apc_list":null,"apc_paid":null,"fwci":1.3494,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.83071648,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"33","issue":null,"first_page":"2746","last_page":"2751"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9998999834060669,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9998000264167786,"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":0.9753999710083008,"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":0.8271781206130981},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7356041669845581},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.6604752540588379},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.6559888124465942},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.6485039591789246},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6337563395500183},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5914022326469421},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5196143984794617},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.49628573656082153},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3379824161529541},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3292219638824463}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8271781206130981},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7356041669845581},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.6604752540588379},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.6559888124465942},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.6485039591789246},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6337563395500183},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5914022326469421},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5196143984794617},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.49628573656082153},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3379824161529541},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3292219638824463},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2016.7900051","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7900051","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1500711968","https://openalex.org/W1702419847","https://openalex.org/W1928739709","https://openalex.org/W1952857803","https://openalex.org/W1990947293","https://openalex.org/W2022508996","https://openalex.org/W2044235398","https://openalex.org/W2049996926","https://openalex.org/W2060280062","https://openalex.org/W2064675550","https://openalex.org/W2075156252","https://openalex.org/W2084455417","https://openalex.org/W2093414253","https://openalex.org/W2100642335","https://openalex.org/W2113325037","https://openalex.org/W2137940226","https://openalex.org/W2157331557","https://openalex.org/W2159756630","https://openalex.org/W2163605009","https://openalex.org/W2210697964","https://openalex.org/W2210749627","https://openalex.org/W2212742183","https://openalex.org/W2214145768","https://openalex.org/W2218414108","https://openalex.org/W2264178313","https://openalex.org/W2296174593","https://openalex.org/W2919115771","https://openalex.org/W6637606113","https://openalex.org/W6684191040","https://openalex.org/W6693305720"],"related_works":["https://openalex.org/W4225394202","https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W1847088711","https://openalex.org/W3036642985","https://openalex.org/W3032952384","https://openalex.org/W3017902212","https://openalex.org/W2964335273","https://openalex.org/W2982145560","https://openalex.org/W2964954556"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,109],"propose":[4],"two":[5,134],"new":[6,46],"approaches":[7,155],"using":[8,69],"the":[9,15,34,50,75,81,88,95,118,157,163],"Convolution":[10],"Neural":[11,17],"Network":[12,18],"(CNN)":[13],"and":[14,103,140,142,160],"Recurrent":[16],"(RNN)":[19],"for":[20],"tracking":[21,61,113,148],"3D":[22,85,167],"hand":[23,136,147,168],"poses.":[24],"The":[25],"first":[26,42],"approach":[27,62],"is":[28,36,44,74,131],"a":[29,37,45,58,84,98],"detection":[30,55,120],"based":[31,52],"algorithm":[32],"while":[33],"second":[35,72],"data":[38],"driven":[39],"method.":[40],"Our":[41,71,128],"contribution":[43,73],"tracking-by-detection":[47],"strategy":[48],"extending":[49],"CNN":[51],"single":[53],"frame":[54,60],"method":[56,130],"to":[57,79,87,93,126],"multiple":[59],"by":[63],"taking":[64],"into":[65],"account":[66],"prediction":[67],"history":[68],"RNN.":[70],"use":[76],"of":[77,83,97,166],"RNN":[78],"simulate":[80],"fitting":[82,101],"model":[86],"input":[89],"data.":[90],"It":[91],"helps":[92],"relax":[94],"need":[96],"carefully":[99],"designed":[100],"function":[102],"optimization":[104],"algorithm.":[105],"With":[106],"such":[107],"strategies,":[108],"show":[110,152],"that":[111,153],"our":[112,154],"frameworks":[114],"can":[115],"automatically":[116],"correct":[117],"fail":[119],"made":[121],"in":[122,162],"previous":[123],"frames":[124],"due":[125],"occlusions.":[127],"proposed":[129],"evaluated":[132],"on":[133],"public":[135],"datasets,":[137],"i.e.":[138],"NYU":[139],"ICVL,":[141],"compared":[143],"against":[144],"other":[145],"recent":[146],"methods.":[149],"Experimental":[150],"results":[151],"achieve":[156],"state-of-the-art":[158],"accuracy":[159],"efficiency":[161],"challenging":[164],"problem":[165],"pose":[169],"estimation.":[170]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
