{"id":"https://openalex.org/W2737528646","doi":"https://doi.org/10.1109/icra.2017.7989303","title":"Learning a deep network with spherical part model for 3D hand pose estimation","display_name":"Learning a deep network with spherical part model for 3D hand pose estimation","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2737528646","doi":"https://doi.org/10.1109/icra.2017.7989303","mag":"2737528646"},"language":"en","primary_location":{"id":"doi:10.1109/icra.2017.7989303","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2017.7989303","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Robotics and Automation (ICRA)","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/A5058284526","display_name":"Tzu-Yang Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Tzu-Yang Chen","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Taiwan University, Taiwan, ROC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Taiwan University, Taiwan, ROC","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001504366","display_name":"Pai-Wen Ting","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Pai-Wen Ting","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Taiwan University, Taiwan, ROC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Taiwan University, Taiwan, ROC","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101361944","display_name":"Min-Yu Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Min-Yu Wu","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Taiwan University, Taiwan, ROC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Taiwan University, Taiwan, ROC","institution_ids":["https://openalex.org/I16733864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101925654","display_name":"Li\u2010Chen Fu","orcid":"https://orcid.org/0000-0002-6947-7646"},"institutions":[{"id":"https://openalex.org/I16733864","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95","country_code":"TW","type":"education","lineage":["https://openalex.org/I16733864"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Li-Chen Fu","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Taiwan University, Taiwan, ROC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Taiwan University, Taiwan, ROC","institution_ids":["https://openalex.org/I16733864"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I16733864"],"apc_list":null,"apc_paid":null,"fwci":0.7215,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.80282436,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"33","issue":null,"first_page":"2600","last_page":"2605"},"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9998000264167786,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9958999752998352,"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/pose","display_name":"Pose","score":0.8175883293151855},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7992414236068726},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7963745594024658},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6841282248497009},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6557113528251648},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.4982118606567383},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4867822825908661},{"id":"https://openalex.org/keywords/virtual-reality","display_name":"Virtual reality","score":0.47439005970954895},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4578830301761627},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4520225524902344},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4430758059024811},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42475542426109314},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41702988743782043},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09448269009590149}],"concepts":[{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.8175883293151855},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7992414236068726},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7963745594024658},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6841282248497009},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6557113528251648},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.4982118606567383},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4867822825908661},{"id":"https://openalex.org/C194969405","wikidata":"https://www.wikidata.org/wiki/Q170519","display_name":"Virtual reality","level":2,"score":0.47439005970954895},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4578830301761627},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4520225524902344},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4430758059024811},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42475542426109314},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41702988743782043},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09448269009590149},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra.2017.7989303","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2017.7989303","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1441581489","https://openalex.org/W1702419847","https://openalex.org/W1849277567","https://openalex.org/W1968723779","https://openalex.org/W1990947293","https://openalex.org/W2036989445","https://openalex.org/W2056025798","https://openalex.org/W2056898157","https://openalex.org/W2060280062","https://openalex.org/W2075156252","https://openalex.org/W2093414253","https://openalex.org/W2102605133","https://openalex.org/W2109255472","https://openalex.org/W2110619642","https://openalex.org/W2113325037","https://openalex.org/W2131213558","https://openalex.org/W2132928347","https://openalex.org/W2137940226","https://openalex.org/W2145546283","https://openalex.org/W2162254475","https://openalex.org/W2210697964","https://openalex.org/W2214145768","https://openalex.org/W2365383126","https://openalex.org/W2466381304","https://openalex.org/W2608288619","https://openalex.org/W2613718673","https://openalex.org/W2963577185","https://openalex.org/W2963613382","https://openalex.org/W4248936881","https://openalex.org/W6620707391","https://openalex.org/W6628276711","https://openalex.org/W6637606113","https://openalex.org/W6639204139","https://openalex.org/W6669020055"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W4253893311","https://openalex.org/W3133861977","https://openalex.org/W3089306886","https://openalex.org/W2113785214","https://openalex.org/W2798721181","https://openalex.org/W3201205132","https://openalex.org/W4387967917","https://openalex.org/W4312694060"],"abstract_inverted_index":{"3D":[0,64],"hand":[1,65,93,133],"pose":[2,66,79,134,184],"estimation":[3,67,185],"is":[4,46,152,186,191],"a":[5,29,48,63,92,102,120,149],"hot":[6],"research":[7],"topic":[8],"in":[9,16],"recent":[10],"years.":[11],"It's":[12],"been":[13],"widely":[14],"used":[15],"many":[17],"advanced":[18],"applications":[19],"for":[20,32],"virtual":[21],"reality":[22],"and":[23,36,75,100,157,177,190],"human-computer":[24],"interaction,":[25],"since":[26],"it":[27,45],"provides":[28],"natural":[30],"interface":[31],"communication":[33],"between":[34],"human":[35,73,140,169],"cyberspace.":[37],"Despite":[38],"the":[39,53,85,113,144,178,183,194,198],"fast":[40],"development":[41],"of":[42,87,115,139,146,182,197],"this":[43,57,108],"field,":[44],"still":[47],"difficult":[49],"task":[50],"due":[51],"to":[52,61,111,123],"various":[54],"challenges.":[55],"In":[56],"paper,":[58],"we":[59,90,118],"aim":[60],"build":[62],"system":[68,166],"which":[69],"can":[70,129,167],"correctly":[71],"detect":[72,168],"hands":[74,170],"accurately":[76,131],"estimate":[77,132],"its":[78],"using":[80,107],"depth":[81],"images.":[82],"To":[83,142],"guarantee":[84],"robustness":[86],"our":[88,147,165],"system,":[89],"design":[91],"model":[94,98],"called":[95],"spherical":[96],"part":[97],"(SPM),":[99],"train":[101],"deep":[103],"convolutional":[104],"neural":[105],"network":[106,128],"model.":[109],"Moreover,":[110],"reduce":[112],"influence":[114],"human's":[116],"omissions,":[117],"use":[119],"data-driven":[121],"approach":[122],"integrate":[124],"them":[125],"together.":[126],"Our":[127],"more":[130],"based":[135],"on":[136,154],"prior":[137],"knowledge":[138],"hand.":[141],"demonstrate":[143],"superiority":[145],"method,":[148],"complete":[150],"experiment":[151],"conducted":[153],"two":[155],"public":[156],"one":[158],"self-built":[159],"datasets.":[160],"The":[161],"results":[162],"show":[163],"that":[164],"with":[171],"average":[172,179],"precision":[173],"at":[174],"almost":[175],"90%":[176],"error":[180],"distance":[181],"about":[187],"10":[188],"millimeters,":[189],"better":[192],"than":[193],"other":[195],"state":[196],"art":[199],"works.":[200]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}