{"id":"https://openalex.org/W2110812473","doi":"https://doi.org/10.1109/icce.2013.6486844","title":"3D hand gesture recognition from one example","display_name":"3D hand gesture recognition from one example","publication_year":2013,"publication_date":"2013-01-01","ids":{"openalex":"https://openalex.org/W2110812473","doi":"https://doi.org/10.1109/icce.2013.6486844","mag":"2110812473"},"language":"en","primary_location":{"id":"doi:10.1109/icce.2013.6486844","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce.2013.6486844","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Consumer Electronics (ICCE)","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/A5024679227","display_name":"Myoung\u2010Kyu Sohn","orcid":null},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Myoung-Kyu Sohn","raw_affiliation_strings":["Division of IT Convergence, DGIST, South Korea","Div. of IT Convergence, DGIST, Daegu, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of IT Convergence, DGIST, South Korea","institution_ids":["https://openalex.org/I193352282"]},{"raw_affiliation_string":"Div. of IT Convergence, DGIST, Daegu, South Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100653535","display_name":"Sang\u2010Heon Lee","orcid":"https://orcid.org/0000-0002-3655-7981"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sang-Heon Lee","raw_affiliation_strings":["Division of IT Convergence, DGIST, South Korea","Div. of IT Convergence, DGIST, Daegu, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of IT Convergence, DGIST, South Korea","institution_ids":["https://openalex.org/I193352282"]},{"raw_affiliation_string":"Div. of IT Convergence, DGIST, Daegu, South Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038019752","display_name":"Dong\u2010Ju Kim","orcid":"https://orcid.org/0000-0003-1836-2977"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dong-Ju Kim","raw_affiliation_strings":["Division of IT Convergence, DGIST, South Korea","Div. of IT Convergence, DGIST, Daegu, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of IT Convergence, DGIST, South Korea","institution_ids":["https://openalex.org/I193352282"]},{"raw_affiliation_string":"Div. of IT Convergence, DGIST, Daegu, South Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102852082","display_name":"Byung\u2010Min Kim","orcid":"https://orcid.org/0000-0002-2461-2314"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Byungmin Kim","raw_affiliation_strings":["Division of IT Convergence, DGIST, South Korea","Div. of IT Convergence, DGIST, Daegu, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of IT Convergence, DGIST, South Korea","institution_ids":["https://openalex.org/I193352282"]},{"raw_affiliation_string":"Div. of IT Convergence, DGIST, Daegu, South Korea","institution_ids":["https://openalex.org/I193352282"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004082294","display_name":"Hyunduk Kim","orcid":"https://orcid.org/0000-0002-3901-1327"},"institutions":[{"id":"https://openalex.org/I193352282","display_name":"Daegu Gyeongbuk Institute of Science and Technology","ror":"https://ror.org/03frjya69","country_code":"KR","type":"education","lineage":["https://openalex.org/I193352282"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyunduk Kim","raw_affiliation_strings":["Division of IT Convergence, DGIST, South Korea","Div. of IT Convergence, DGIST, Daegu, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of IT Convergence, DGIST, South Korea","institution_ids":["https://openalex.org/I193352282"]},{"raw_affiliation_string":"Div. of IT Convergence, DGIST, Daegu, South Korea","institution_ids":["https://openalex.org/I193352282"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.58,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.84488108,"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":"171","last_page":"172"},"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":0.9708999991416931,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9625999927520752,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/dynamic-time-warping","display_name":"Dynamic time warping","score":0.8940092325210571},{"id":"https://openalex.org/keywords/gesture-recognition","display_name":"Gesture recognition","score":0.8326746225357056},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7946756482124329},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6805540323257446},{"id":"https://openalex.org/keywords/gesture","display_name":"Gesture","score":0.5830498933792114},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5769721865653992},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5658859014511108},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5605716705322266},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5276588201522827},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.5106614232063293},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4289882779121399},{"id":"https://openalex.org/keywords/similarity-measure","display_name":"Similarity measure","score":0.42701563239097595},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.42017969489097595},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15158870816230774},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10195857286453247}],"concepts":[{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.8940092325210571},{"id":"https://openalex.org/C159437735","wikidata":"https://www.wikidata.org/wiki/Q1519524","display_name":"Gesture recognition","level":3,"score":0.8326746225357056},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7946756482124329},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6805540323257446},{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.5830498933792114},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5769721865653992},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5658859014511108},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5605716705322266},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5276588201522827},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.5106614232063293},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4289882779121399},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.42701563239097595},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.42017969489097595},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15158870816230774},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10195857286453247},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce.2013.6486844","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce.2013.6486844","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Consumer Electronics (ICCE)","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":4,"referenced_works":["https://openalex.org/W2055910046","https://openalex.org/W2115733720","https://openalex.org/W2168392347","https://openalex.org/W4255601674"],"related_works":["https://openalex.org/W2315394208","https://openalex.org/W72718568","https://openalex.org/W2318081358","https://openalex.org/W2902873204","https://openalex.org/W2185750513","https://openalex.org/W2032462055","https://openalex.org/W2010878661","https://openalex.org/W2063512338","https://openalex.org/W3147379364","https://openalex.org/W2795192618"],"abstract_inverted_index":{"In":[0],"a":[1,39,63,82,95],"typical":[2],"recognition":[3,16,42],"system,":[4],"the":[5,15,76,88,114],"inclusion":[6],"of":[7],"more":[8],"training":[9,26],"data":[10,111],"is":[11,20,48,60],"likely":[12],"to":[13,23],"increase":[14],"rate.":[17],"However,":[18],"it":[19],"not":[21],"easy":[22],"obtain":[24],"large":[25],"sets.":[27],"Focusing":[28],"on":[29,75,108],"practical":[30],"applicability":[31],"such":[32],"as":[33],"controlling":[34],"home":[35],"appliances,":[36],"we":[37,80],"propose":[38],"hand":[40,57,109],"gesture":[41,110],"method":[43,85],"from":[44,62],"one":[45],"example":[46],"that":[47],"computationally":[49],"efficient":[50],"and":[51,66,94,112],"can":[52],"be":[53],"easily":[54],"implemented.":[55],"3D":[56],"motion":[58],"trajectory":[59],"achieved":[61],"depth":[64],"camera":[65],"then":[67],"normalized":[68],"for":[69,98],"translation":[70],"invariant":[71],"feature":[72],"extraction.":[73],"Based":[74],"simple":[77],"K-NN":[78],"classifier,":[79],"develop":[81],"pattern":[83],"matching":[84],"by":[86],"combining":[87],"DTW":[89,121],"(Dynamic":[90],"Time":[91],"Warping)":[92],"algorithm":[93],"statistical":[96],"measure":[97],"similarity":[99],"between":[100],"two":[101],"random":[102],"vectors.":[103],"We":[104],"conducted":[105],"computational":[106],"experiments":[107],"compared":[113],"results":[115],"with":[116],"those":[117],"derived":[118],"via":[119],"conventional":[120],"recognition.":[122]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}