{"id":"https://openalex.org/W4321020585","doi":"https://doi.org/10.1109/sii55687.2023.10039372","title":"Pointing Gesture Interface with Fovea-Lens Camera by Deep Learning using Skeletal Information","display_name":"Pointing Gesture Interface with Fovea-Lens Camera by Deep Learning using Skeletal Information","publication_year":2023,"publication_date":"2023-01-17","ids":{"openalex":"https://openalex.org/W4321020585","doi":"https://doi.org/10.1109/sii55687.2023.10039372"},"language":"en","primary_location":{"id":"doi:10.1109/sii55687.2023.10039372","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sii55687.2023.10039372","pdf_url":null,"source":{"id":"https://openalex.org/S4363605654","display_name":"2023 IEEE/SICE International Symposium on System Integration (SII)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/SICE International Symposium on System Integration (SII)","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/A5050224377","display_name":"Takahiro Ikeda","orcid":"https://orcid.org/0000-0003-4420-7778"},"institutions":[{"id":"https://openalex.org/I42405503","display_name":"Gifu University","ror":"https://ror.org/024exxj48","country_code":"JP","type":"education","lineage":["https://openalex.org/I42405503"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Takahiro Ikeda","raw_affiliation_strings":["Gifu University,Department of Mechanical Engineering,Gifu,Japan","Department of Mechanical Engineering, Gifu University, Gifu, Japan"],"affiliations":[{"raw_affiliation_string":"Gifu University,Department of Mechanical Engineering,Gifu,Japan","institution_ids":["https://openalex.org/I42405503"]},{"raw_affiliation_string":"Department of Mechanical Engineering, Gifu University, Gifu, Japan","institution_ids":["https://openalex.org/I42405503"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023302733","display_name":"Satoshi Ueki","orcid":null},"institutions":[{"id":"https://openalex.org/I42405503","display_name":"Gifu University","ror":"https://ror.org/024exxj48","country_code":"JP","type":"education","lineage":["https://openalex.org/I42405503"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Satoshi Ueki","raw_affiliation_strings":["Gifu University,Department of Mechanical Engineering,Gifu,Japan","Department of Mechanical Engineering, Gifu University, Gifu, Japan"],"affiliations":[{"raw_affiliation_string":"Gifu University,Department of Mechanical Engineering,Gifu,Japan","institution_ids":["https://openalex.org/I42405503"]},{"raw_affiliation_string":"Department of Mechanical Engineering, Gifu University, Gifu, Japan","institution_ids":["https://openalex.org/I42405503"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108416899","display_name":"Hironao YAMADA","orcid":null},"institutions":[{"id":"https://openalex.org/I42405503","display_name":"Gifu University","ror":"https://ror.org/024exxj48","country_code":"JP","type":"education","lineage":["https://openalex.org/I42405503"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hironao Yamada","raw_affiliation_strings":["Gifu University,Department of Mechanical Engineering,Gifu,Japan","Department of Mechanical Engineering, Gifu University, Gifu, Japan"],"affiliations":[{"raw_affiliation_string":"Gifu University,Department of Mechanical Engineering,Gifu,Japan","institution_ids":["https://openalex.org/I42405503"]},{"raw_affiliation_string":"Department of Mechanical Engineering, Gifu University, Gifu, Japan","institution_ids":["https://openalex.org/I42405503"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5050224377"],"corresponding_institution_ids":["https://openalex.org/I42405503"],"apc_list":null,"apc_paid":null,"fwci":0.235,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.33928571,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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":0.9988999962806702,"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":0.9951000213623047,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8279034495353699},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.786410927772522},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.767384946346283},{"id":"https://openalex.org/keywords/lens","display_name":"Lens (geology)","score":0.6231043338775635},{"id":"https://openalex.org/keywords/gesture","display_name":"Gesture","score":0.614304780960083},{"id":"https://openalex.org/keywords/interface","display_name":"Interface (matter)","score":0.5620518326759338},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.5196041464805603},{"id":"https://openalex.org/keywords/hand-position","display_name":"Hand position","score":0.47670572996139526},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.45416954159736633},{"id":"https://openalex.org/keywords/gesture-recognition","display_name":"Gesture recognition","score":0.4403440058231354},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4335729777812958},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.15202251076698303},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.0689145028591156}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8279034495353699},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.786410927772522},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.767384946346283},{"id":"https://openalex.org/C15336307","wikidata":"https://www.wikidata.org/wiki/Q1766051","display_name":"Lens (geology)","level":2,"score":0.6231043338775635},{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.614304780960083},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.5620518326759338},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.5196041464805603},{"id":"https://openalex.org/C3018151503","wikidata":"https://www.wikidata.org/wiki/Q608487","display_name":"Hand position","level":2,"score":0.47670572996139526},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.45416954159736633},{"id":"https://openalex.org/C159437735","wikidata":"https://www.wikidata.org/wiki/Q1519524","display_name":"Gesture recognition","level":3,"score":0.4403440058231354},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4335729777812958},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.15202251076698303},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0689145028591156},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0},{"id":"https://openalex.org/C129307140","wikidata":"https://www.wikidata.org/wiki/Q6795880","display_name":"Maximum bubble pressure method","level":3,"score":0.0},{"id":"https://openalex.org/C157915830","wikidata":"https://www.wikidata.org/wiki/Q2928001","display_name":"Bubble","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sii55687.2023.10039372","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sii55687.2023.10039372","pdf_url":null,"source":{"id":"https://openalex.org/S4363605654","display_name":"2023 IEEE/SICE International Symposium on System Integration (SII)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/SICE International Symposium on System Integration (SII)","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":15,"referenced_works":["https://openalex.org/W1869758581","https://openalex.org/W2056510510","https://openalex.org/W2144807120","https://openalex.org/W2146187731","https://openalex.org/W2324912663","https://openalex.org/W2559085405","https://openalex.org/W2592523922","https://openalex.org/W2612622881","https://openalex.org/W2914852005","https://openalex.org/W3009130550","https://openalex.org/W3016541531","https://openalex.org/W3102151175","https://openalex.org/W4205559380","https://openalex.org/W4221046430","https://openalex.org/W6639229959"],"related_works":["https://openalex.org/W2902873204","https://openalex.org/W2185750513","https://openalex.org/W4312416068","https://openalex.org/W3147379364","https://openalex.org/W2010878661","https://openalex.org/W2026258298","https://openalex.org/W3204639664","https://openalex.org/W2970836791","https://openalex.org/W2805039731","https://openalex.org/W2989699735"],"abstract_inverted_index":{"This":[0,22],"paper":[1],"describes":[2],"a":[3,16,66,154,161,166],"pointing":[4,35,37,95,123],"gesture":[5,27,79,112],"interface":[6,23,41],"based":[7,71],"on":[8,72],"deep":[9,98],"learning":[10,99],"using":[11,100,153,160],"RGB":[12],"images":[13,51],"acquired":[14,52],"by":[15,97],"fovea":[17,55,155],"lens":[18,56,156,163,168],"camera":[19,139,157,164,169],"as":[20,105],"input.":[21,106],"consists":[24],"of":[25,62,88,117,129,152],"hand":[26,67,78,111],"recognition":[28,80,113],"to":[29,45,96,159],"determine":[30],"if":[31],"the":[32,47,54,60,73,84,89,92,101,135,138,141,148],"operator":[33,93,142],"is":[34,69,81,94],"and":[36,77,140,150,165],"position":[38,124],"estimation.":[39],"The":[40,122],"first":[42],"uses":[43],"OpenPose":[44],"estimate":[46],"operator's":[48],"skeleton":[49],"from":[50],"with":[53],"camera,":[57],"which":[58,87],"mimics":[59],"characteristics":[61],"human":[63],"vision.":[64],"Next,":[65],"image":[68],"cropped":[70],"estimated":[74,102],"wrist":[75],"coordinates,":[76],"performed.":[82],"Then,":[83],"system":[85],"classifies":[86],"pre-defined":[90],"positions":[91,104],"joint":[103],"Evaluation":[107],"experiments":[108],"showed":[109],"that":[110],"achieved":[114,126],"an":[115,127],"accuracy":[116,128],"more":[118,130],"than":[119,131],"95":[120],"%.":[121],"estimation":[125],"85":[132],"%":[133],"when":[134],"distance":[136],"between":[137],"was":[143],"3":[144],"m.":[145],"In":[146],"addition,":[147],"advantages":[149],"challenges":[151],"compared":[158],"standard":[162],"wide-angle":[167],"were":[170],"discussed.":[171]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}