{"id":"https://openalex.org/W2909828897","doi":"https://doi.org/10.1109/iros.2018.8593433","title":"Learned Hand Gesture Classification Through Synthetically Generated Training Samples","display_name":"Learned Hand Gesture Classification Through Synthetically Generated Training Samples","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2909828897","doi":"https://doi.org/10.1109/iros.2018.8593433","mag":"2909828897"},"language":"en","primary_location":{"id":"doi:10.1109/iros.2018.8593433","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2018.8593433","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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/A5073480368","display_name":"Kyle Lindgren","orcid":"https://orcid.org/0000-0002-8216-074X"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Kyle Lindgren","raw_affiliation_strings":["Dept. of Electrical Engineering, University of Washington, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Dept. of Electrical Engineering, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063594993","display_name":"Niveditha Kalavakonda","orcid":"https://orcid.org/0000-0001-7578-4696"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Niveditha Kalavakonda","raw_affiliation_strings":["Dept. of Electrical Engineering, University of Washington, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Dept. of Electrical Engineering, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041002946","display_name":"David Caballero","orcid":"https://orcid.org/0000-0003-2165-0726"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David E. Caballero","raw_affiliation_strings":["Dept. of Electrical Engineering, University of Washington, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Dept. of Electrical Engineering, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062032121","display_name":"Kevin Huang","orcid":"https://orcid.org/0000-0002-0300-9911"},"institutions":[{"id":"https://openalex.org/I56722557","display_name":"Trinity College","ror":"https://ror.org/03j3dbz94","country_code":"US","type":"education","lineage":["https://openalex.org/I56722557"]},{"id":"https://openalex.org/I4401726811","display_name":"Hartford Financial Services (United States)","ror":"https://ror.org/00mwq1g96","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726811"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kevin Huang","raw_affiliation_strings":["Trinity College, Dept. of Engineering, Hartford, CT, USA"],"affiliations":[{"raw_affiliation_string":"Trinity College, Dept. of Engineering, Hartford, CT, USA","institution_ids":["https://openalex.org/I56722557","https://openalex.org/I4401726811"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074967911","display_name":"Blake Hannaford","orcid":"https://orcid.org/0000-0001-7370-4920"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Blake Hannaford","raw_affiliation_strings":["Dept. of Electrical Engineering, University of Washington, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"Dept. of Electrical Engineering, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5073480368"],"corresponding_institution_ids":["https://openalex.org/I201448701"],"apc_list":null,"apc_paid":null,"fwci":0.5433,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.68677196,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"3937","last_page":"3942"},"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9932000041007996,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.9884999990463257,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/gesture","display_name":"Gesture","score":0.8931138515472412},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8422002792358398},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6873740553855896},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5867964029312134},{"id":"https://openalex.org/keywords/gesture-recognition","display_name":"Gesture recognition","score":0.5817477703094482},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5614592432975769},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.4822150468826294},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43185606598854065}],"concepts":[{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.8931138515472412},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8422002792358398},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6873740553855896},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5867964029312134},{"id":"https://openalex.org/C159437735","wikidata":"https://www.wikidata.org/wiki/Q1519524","display_name":"Gesture recognition","level":3,"score":0.5817477703094482},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5614592432975769},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4822150468826294},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43185606598854065},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros.2018.8593433","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2018.8593433","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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":24,"referenced_works":["https://openalex.org/W1525830374","https://openalex.org/W1590183771","https://openalex.org/W1755904634","https://openalex.org/W1901616594","https://openalex.org/W1943054406","https://openalex.org/W1974588631","https://openalex.org/W2036576795","https://openalex.org/W2102178824","https://openalex.org/W2119656522","https://openalex.org/W2120725061","https://openalex.org/W2121439273","https://openalex.org/W2128010288","https://openalex.org/W2145835757","https://openalex.org/W2152988638","https://openalex.org/W2161969291","https://openalex.org/W2481999338","https://openalex.org/W2615547864","https://openalex.org/W2775795276","https://openalex.org/W2782816442","https://openalex.org/W2787779682","https://openalex.org/W2963709863","https://openalex.org/W6637959944","https://openalex.org/W6681579763","https://openalex.org/W6683411478"],"related_works":["https://openalex.org/W2066003895","https://openalex.org/W2902873204","https://openalex.org/W2185750513","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":{"Hand":[0],"gestures":[1,11,60],"are":[2,12,81],"a":[3,26,74,141,179],"natural":[4],"component":[5],"of":[6,144],"human-human":[7],"communication.":[8],"Simple":[9],"hand":[10,59,105,146,181],"intuitive":[13,37],"and":[14,39,44,48,54,86,91,125,165,174],"can":[15,30,113],"exhibit":[16],"great":[17],"lexical":[18],"variety.":[19],"It":[20],"stands":[21],"to":[22,41,97,177],"reason":[23],"that":[24,89,136,150,159,184],"such":[25],"user":[27,118],"input":[28],"mechanism":[29],"have":[31],"many":[32],"benefits,":[33],"including":[34],"seamless":[35],"interaction,":[36],"control":[38],"robustness":[40],"physical":[42,168],"constraints":[43],"ambient":[45],"electrical,":[46],"light":[47],"sound":[49],"interference.":[50],"However,":[51],"while":[52],"semantic":[53],"logical":[55],"information":[56],"encoded":[57],"via":[58,117],"is":[61,102,123,133,171],"readily":[62],"decoded":[63],"by":[64],"humans,":[65],"leveraging":[66],"this":[67,138],"communication":[68],"channel":[69],"in":[70,186],"human-machine":[71],"interfaces":[72],"remains":[73],"challenge.":[75],"Recent":[76],"data-driven":[77],"deep":[78],"learning":[79],"approaches":[80],"promising":[82],"towards":[83,104],"uncovering":[84],"abstract":[85],"complex":[87],"relationships":[88],"manual":[90],"direct":[92],"rule-based":[93],"classification":[94],"schemes":[95],"fail":[96],"discover.":[98],"Such":[99],"an":[100],"approach":[101,129],"amenable":[103],"gesture":[106,147,182],"recognition,":[107],"but":[108],"requires":[109],"myriad":[110],"data":[111,169],"which":[112],"be":[114],"collected":[115],"physically":[116],"experiments.":[119],"This":[120],"process,":[121],"however,":[122],"onerous":[124],"tedious.":[126],"A":[127],"streamlined":[128],"with":[130],"less":[131],"overhead":[132],"sought.":[134],"To":[135],"end,":[137],"work":[139],"presents":[140],"novel":[142],"method":[143],"synthetic":[145,164],"dataset":[148],"generation":[149],"leverages":[151],"modern":[152],"gaming":[153],"engines.":[154],"Furthermore,":[155],"preliminary":[156],"results":[157],"indicate":[158],"the":[160],"dataset,":[161],"despite":[162],"being":[163],"requiring":[166],"no":[167],"collection,":[170],"both":[172],"accurate":[173],"rich":[175],"enough":[176],"train":[178],"real-world":[180],"classifier":[183],"operates":[185],"real-time.":[187]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}