{"id":"https://openalex.org/W2902159119","doi":"https://doi.org/10.1145/3281505.3281592","title":"Estimation of distance between thumb and forefinger from hand dorsal image using deep learning","display_name":"Estimation of distance between thumb and forefinger from hand dorsal image using deep learning","publication_year":2018,"publication_date":"2018-11-28","ids":{"openalex":"https://openalex.org/W2902159119","doi":"https://doi.org/10.1145/3281505.3281592","mag":"2902159119"},"language":"en","primary_location":{"id":"doi:10.1145/3281505.3281592","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3281505.3281592","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM Symposium on Virtual Reality Software and Technology","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/A5048952969","display_name":"Takuma Shimizume","orcid":null},"institutions":[{"id":"https://openalex.org/I159385669","display_name":"Chiba University","ror":"https://ror.org/01hjzeq58","country_code":"JP","type":"education","lineage":["https://openalex.org/I159385669"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Takuma Shimizume","raw_affiliation_strings":["Chiba University, Chiba, Japan"],"affiliations":[{"raw_affiliation_string":"Chiba University, Chiba, Japan","institution_ids":["https://openalex.org/I159385669"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079809394","display_name":"Takeshi Umezawa","orcid":"https://orcid.org/0000-0001-5972-0377"},"institutions":[{"id":"https://openalex.org/I159385669","display_name":"Chiba University","ror":"https://ror.org/01hjzeq58","country_code":"JP","type":"education","lineage":["https://openalex.org/I159385669"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takeshi Umezawa","raw_affiliation_strings":["Chiba University, Chiba, Japan"],"affiliations":[{"raw_affiliation_string":"Chiba University, Chiba, Japan","institution_ids":["https://openalex.org/I159385669"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081277220","display_name":"Noritaka Osawa","orcid":"https://orcid.org/0000-0002-7676-9911"},"institutions":[{"id":"https://openalex.org/I159385669","display_name":"Chiba University","ror":"https://ror.org/01hjzeq58","country_code":"JP","type":"education","lineage":["https://openalex.org/I159385669"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Noritaka Osawa","raw_affiliation_strings":["Chiba University, Chiba, Japan"],"affiliations":[{"raw_affiliation_string":"Chiba University, Chiba, Japan","institution_ids":["https://openalex.org/I159385669"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5048952969"],"corresponding_institution_ids":["https://openalex.org/I159385669"],"apc_list":null,"apc_paid":null,"fwci":0.3622,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.616744,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":1.0,"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":1.0,"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":0.9868999719619751,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9865999817848206,"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/thumb","display_name":"Thumb","score":0.8065336346626282},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8023463487625122},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.689018189907074},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.6762414574623108},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6673052310943604},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6332186460494995},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5485780835151672},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45681440830230713},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44679194688796997},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.43138277530670166},{"id":"https://openalex.org/keywords/rectangle","display_name":"Rectangle","score":0.42086362838745117},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41892603039741516},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2672174572944641},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2649478614330292},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09726747870445251}],"concepts":[{"id":"https://openalex.org/C2776881184","wikidata":"https://www.wikidata.org/wiki/Q83360","display_name":"Thumb","level":2,"score":0.8065336346626282},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8023463487625122},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.689018189907074},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.6762414574623108},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6673052310943604},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6332186460494995},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5485780835151672},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45681440830230713},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44679194688796997},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.43138277530670166},{"id":"https://openalex.org/C2781302577","wikidata":"https://www.wikidata.org/wiki/Q209","display_name":"Rectangle","level":2,"score":0.42086362838745117},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41892603039741516},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2672174572944641},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2649478614330292},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09726747870445251},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C105702510","wikidata":"https://www.wikidata.org/wiki/Q514","display_name":"Anatomy","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/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3281505.3281592","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3281505.3281592","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM Symposium on Virtual Reality Software and Technology","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":3,"referenced_works":["https://openalex.org/W2160633079","https://openalex.org/W2618530766","https://openalex.org/W2771471422"],"related_works":["https://openalex.org/W2242098268","https://openalex.org/W4244945894","https://openalex.org/W4224881918","https://openalex.org/W2003462717","https://openalex.org/W2802042052","https://openalex.org/W174828583","https://openalex.org/W1987609185","https://openalex.org/W2321986606","https://openalex.org/W2059098648","https://openalex.org/W1976660375"],"abstract_inverted_index":{"A":[0,100],"three-dimensional":[1,36],"virtual":[2],"object":[3],"can":[4,90],"be":[5,91,158],"manipulated":[6],"by":[7],"hand":[8,15,30,46,60,81,96],"and":[9,40,112],"finger":[10],"movements":[11],"with":[12],"an":[13,67,159],"optical":[14,68],"tracking":[16],"device":[17],"where":[18,162],"it":[19],"is":[20,33,49,64,164],"necessary":[21],"to":[22,54,177],"recognize":[23],"a":[24,41,56,62,77,80,86,105,117,140,165],"posture":[25,31,57,78],"of":[26,38,44,58,76,79,85,109,132,136,173],"one's":[27],"hand.":[28],"Conventional":[29],"recognition":[32],"based":[34,138],"on":[35,82,139,142],"coordinates":[37],"fingertips":[39,108],"skeletal":[42],"model":[43,102,141,176],"the":[45,59,74,83,95,110,126,143,154,171,174],"[1].":[47],"It":[48],"difficult":[50],"for":[51],"conventional":[52],"methods":[53],"estimate":[55],"when":[61,94],"fingertip":[63],"hidden":[65],"from":[66],"camera.":[69],"This":[70,123,167],"study,":[71],"therefore,":[72],"proposes":[73],"estimation":[75,137],"basis":[84],"hand-dorsal":[87],"image":[88],"that":[89,103,153],"taken":[92],"even":[93],"occludes":[97],"its":[98],"fingertips.":[99],"regression":[101],"estimates":[104],"distance":[106],"between":[107],"thumb":[111],"forefinger":[113],"was":[114,146],"constructed":[115],"using":[116],"convolution":[118],"neural":[119],"network":[120],"(CNN)":[121],"[2].":[122],"work":[124],"evaluated":[125],"root":[127],"mean":[128],"squared":[129],"error":[130],"(RMSE)":[131],"estimation.":[133],"The":[134],"RMSE":[135],"same":[144],"day":[145],"less":[147],"than":[148],"1.8":[149],"mm,":[150],"which":[151],"shows":[152],"proposed":[155],"method":[156,161],"could":[157],"effective":[160],"self-occlusion":[163],"problem.":[166],"study":[168],"also":[169],"evaluates":[170],"robustness":[172],"learning":[175],"time-variation.":[178]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
