{"id":"https://openalex.org/W3022899210","doi":"https://doi.org/10.1145/3293353.3293421","title":"Dynamic Hand Gesture Recognition using Convolutional Neural Network with RGB-D Fusion","display_name":"Dynamic Hand Gesture Recognition using Convolutional Neural Network with RGB-D Fusion","publication_year":2018,"publication_date":"2018-12-18","ids":{"openalex":"https://openalex.org/W3022899210","doi":"https://doi.org/10.1145/3293353.3293421","mag":"3022899210"},"language":"en","primary_location":{"id":"doi:10.1145/3293353.3293421","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3293353.3293421","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 11th Indian Conference on Computer Vision, Graphics and Image Processing","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/A5056245252","display_name":"Bindu Verma","orcid":"https://orcid.org/0000-0003-3534-3364"},"institutions":[{"id":"https://openalex.org/I152429107","display_name":"Jawaharlal Nehru University","ror":"https://ror.org/0567v8t28","country_code":"IN","type":"education","lineage":["https://openalex.org/I152429107"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Bindu Verma","raw_affiliation_strings":["School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, Delhi"],"affiliations":[{"raw_affiliation_string":"School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, Delhi","institution_ids":["https://openalex.org/I152429107"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030506227","display_name":"Ayesha Choudhary","orcid":"https://orcid.org/0000-0002-7544-4912"},"institutions":[{"id":"https://openalex.org/I152429107","display_name":"Jawaharlal Nehru University","ror":"https://ror.org/0567v8t28","country_code":"IN","type":"education","lineage":["https://openalex.org/I152429107"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ayesha Choudhary","raw_affiliation_strings":["School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, Delhi"],"affiliations":[{"raw_affiliation_string":"School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, Delhi","institution_ids":["https://openalex.org/I152429107"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5056245252"],"corresponding_institution_ids":["https://openalex.org/I152429107"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.27209004,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"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":0.9979000091552734,"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/T11285","display_name":"Hearing Impairment and Communication","score":0.9828000068664551,"subfield":{"id":"https://openalex.org/subfields/3204","display_name":"Developmental and Educational Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/gesture","display_name":"Gesture","score":0.8485573530197144},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7836141586303711},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7022146582603455},{"id":"https://openalex.org/keywords/gesture-recognition","display_name":"Gesture recognition","score":0.7000472545623779},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6920321583747864},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6678285598754883},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5726200938224792},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.48044702410697937},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41591185331344604}],"concepts":[{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.8485573530197144},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7836141586303711},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7022146582603455},{"id":"https://openalex.org/C159437735","wikidata":"https://www.wikidata.org/wiki/Q1519524","display_name":"Gesture recognition","level":3,"score":0.7000472545623779},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6920321583747864},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6678285598754883},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5726200938224792},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.48044702410697937},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41591185331344604}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3293353.3293421","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3293353.3293421","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 11th Indian Conference on Computer Vision, Graphics and Image Processing","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":21,"referenced_works":["https://openalex.org/W1944630830","https://openalex.org/W1966846860","https://openalex.org/W1969595749","https://openalex.org/W1985891935","https://openalex.org/W1993666393","https://openalex.org/W1999442188","https://openalex.org/W2002381827","https://openalex.org/W2006347227","https://openalex.org/W2068611653","https://openalex.org/W2126698653","https://openalex.org/W2149645715","https://openalex.org/W2168392347","https://openalex.org/W2219948256","https://openalex.org/W2467634805","https://openalex.org/W2595328592","https://openalex.org/W2769039400","https://openalex.org/W2777985171","https://openalex.org/W2797095726","https://openalex.org/W2917888609","https://openalex.org/W4236965008","https://openalex.org/W4256229258"],"related_works":["https://openalex.org/W2902873204","https://openalex.org/W2185750513","https://openalex.org/W4226493464","https://openalex.org/W2010878661","https://openalex.org/W3147379364","https://openalex.org/W2026258298","https://openalex.org/W3133861977","https://openalex.org/W3204639664","https://openalex.org/W2970836791","https://openalex.org/W2989699735"],"abstract_inverted_index":{"In":[0,73],"this":[1],"paper,":[2],"we":[3,77,91,139,183],"propose":[4],"a":[5,26],"novel,":[6],"real-time":[7],"dynamic":[8,87,171,202,224,236],"hand":[9,58,62,88,172,203,225,237],"gesture":[10,106,130,173,238],"recognition":[11,174],"framework":[12],"using":[13,153,163,177,215],"convolutional":[14],"neural":[15],"network":[16,150,160],"with":[17,93,108,113],"depth":[18,82,96,114,164,197],"and":[19,38,54,66,68,81,95,111,196,220,232,240],"RGB":[20,80,94,109,154,195],"data":[21,83,97,110,115,198],"fusion.":[22],"Hand":[23],"gestures":[24,59],"are":[25,60,69],"natural":[27],"form":[28],"of":[29,104,121,127,135,187,247],"communication":[30],"between":[31,36],"humans":[32],"as":[33,35,48],"well":[34],"human":[37],"machine.":[39],"They":[40],"also":[41],"find":[42,100],"important":[43],"applications":[44],"in":[45,64],"areas":[46],"such":[47],"sign":[49],"language":[50],"recognition,":[51],"man-machine":[52],"interaction":[53],"behavior":[55],"understanding.":[56],"Natural":[57],"complex":[61],"movements":[63],"space":[65],"time":[67],"challenging":[70],"to":[71,84,116,167,218],"recognize.":[72],"our":[74,243],"proposed":[75],"framework,":[76],"use":[78,140],"both":[79,188,212],"automatically":[85],"recognize":[86,222],"gestures.":[89],"Initially,":[90],"work":[92],"separately.":[98],"We":[99,205,227],"the":[101,105,118,122,128,132,136,158,178,185,189,208,213,223,233,248],"motion":[102,119,155,165,190],"history":[103,126,156,191],"performed":[107,129],"independently":[112],"store":[117],"information":[120,134],"moving":[123],"hands.":[124],"Motion":[125],"stores":[131],"rich":[133],"movement.":[137],"Then,":[138,176],"transfer":[141],"learning":[142],"on":[143,230],"two":[144,179],"separate":[145],"VGG16":[146,181],"networks,":[147,182],"where":[148],"one":[149],"is":[151,161],"fine-tuned":[152,162],"while":[157],"other":[159],"history,":[166],"configure":[168],"them":[169],"for":[170,200],"problem.":[175],"fine-tunned":[180],"extract":[184],"features":[186,209],"images":[192],"obtained":[193,210],"from":[194,211],"separately,":[199],"each":[201],"gesture.":[204,226],"then,":[206],"integrate":[207],"networks":[214],"weighted":[216],"summation,":[217],"accurately":[219],"robustly":[221],"perform":[228],"experiments":[229],"standard":[231],"publicly":[234],"available":[235],"datasets":[239],"show":[241],"that":[242],"method":[244],"outperforms":[245],"state":[246],"art":[249],"methods.":[250]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
