{"id":"https://openalex.org/W7141026916","doi":"https://doi.org/10.1109/icce67443.2026.11449850","title":"A Real-Time Deep Learning Framework for Sparring Point Detection","display_name":"A Real-Time Deep Learning Framework for Sparring Point Detection","publication_year":2026,"publication_date":"2026-02-03","ids":{"openalex":"https://openalex.org/W7141026916","doi":"https://doi.org/10.1109/icce67443.2026.11449850"},"language":null,"primary_location":{"id":"doi:10.1109/icce67443.2026.11449850","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce67443.2026.11449850","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 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/A5130767404","display_name":"Elizabeth Major","orcid":null},"institutions":[{"id":"https://openalex.org/I67031392","display_name":"Carleton University","ror":"https://ror.org/02qtvee93","country_code":"CA","type":"education","lineage":["https://openalex.org/I67031392"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Elizabeth Major","raw_affiliation_strings":["Carleton University,The School of Information Technology,Ottawa,Canada"],"affiliations":[{"raw_affiliation_string":"Carleton University,The School of Information Technology,Ottawa,Canada","institution_ids":["https://openalex.org/I67031392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130777832","display_name":"David Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I67031392","display_name":"Carleton University","ror":"https://ror.org/02qtvee93","country_code":"CA","type":"education","lineage":["https://openalex.org/I67031392"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"David Liu","raw_affiliation_strings":["Carleton University,The School of Information Technology,Ottawa,Canada"],"affiliations":[{"raw_affiliation_string":"Carleton University,The School of Information Technology,Ottawa,Canada","institution_ids":["https://openalex.org/I67031392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072288399","display_name":"Hamidreza Sadreazami","orcid":"https://orcid.org/0000-0002-2624-0681"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Hamidreza Sadreazami","raw_affiliation_strings":["McGill University,Bio-Engineering Department,Montreal,Canada"],"affiliations":[{"raw_affiliation_string":"McGill University,Bio-Engineering Department,Montreal,Canada","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029996071","display_name":"Marzieh Amini","orcid":"https://orcid.org/0000-0002-5217-2969"},"institutions":[{"id":"https://openalex.org/I67031392","display_name":"Carleton University","ror":"https://ror.org/02qtvee93","country_code":"CA","type":"education","lineage":["https://openalex.org/I67031392"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Marzieh Amini","raw_affiliation_strings":["Carleton University,The Department of System and Computer Engineering,Ottawa,Canada"],"affiliations":[{"raw_affiliation_string":"Carleton University,The Department of System and Computer Engineering,Ottawa,Canada","institution_ids":["https://openalex.org/I67031392"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5130767404"],"corresponding_institution_ids":["https://openalex.org/I67031392"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.94021836,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.20389999449253082,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.20389999449253082,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.09359999746084213,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.04729999974370003,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/deep-learning","display_name":"Deep learning","score":0.6711999773979187},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4447999894618988},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3147999942302704},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.31290000677108765},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.295199990272522},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.28029999136924744}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6876000165939331},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6711999773979187},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5282999873161316},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4447999894618988},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.323199987411499},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3147999942302704},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.31290000677108765},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.295199990272522},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.28029999136924744},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2773999869823456},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2687999904155731},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.26600000262260437},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2547000050544739},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.25270000100135803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce67443.2026.11449850","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce67443.2026.11449850","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 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":9,"referenced_works":["https://openalex.org/W2597933512","https://openalex.org/W2963150697","https://openalex.org/W3004285782","https://openalex.org/W3086712991","https://openalex.org/W3100267739","https://openalex.org/W3120599689","https://openalex.org/W3132920518","https://openalex.org/W4254662100","https://openalex.org/W4392663459"],"related_works":[],"abstract_inverted_index":{"Object":[0],"detection":[1,71,105,115,153,166,190],"and":[2,22,34,72,87,106,114,132,145,148,151,200,226],"tracking":[3,73,80,107],"are":[4,37,117,193],"implemented":[5,98],"for":[6,222],"various":[7],"applications":[8,12],"in":[9,17,29,56,99,135,215],"industry.":[10],"These":[11],"range":[13],"from":[14,245],"camera":[15],"surveillance":[16],"buildings,":[18],"monitoring":[19],"highway":[20],"traffic,":[21],"analyzing":[23],"sports":[24,30],"events.":[25],"In":[26,43,60,77],"its":[27],"application":[28],"like":[31],"soccer,":[32],"basketball,":[33],"football,":[35],"players":[36],"tracked":[38,51],"across":[39],"the":[40,57,165,168,172,180,184,203,206,234],"playing":[41,58],"area.":[42,59],"such":[44],"cases,":[45],"only":[46],"whole":[47,81],"player":[48,82],"motion":[49,83],"is":[50,66,84,97,156,162,178],"to":[52,68,74,108,119,196,237],"analyze":[53],"their":[54,210],"path":[55],"this":[61,100],"work,":[62],"a":[63,121,127,130,133,136,216,223,243,249],"new":[64,122],"method":[65],"proposed":[67],"apply":[69],"object":[70],"sparring":[75,78,94,137],"situations.":[76],"scenarios,":[79],"not":[85],"useful":[86],"individual":[88],"components":[89],"must":[90],"be":[91],"tracked.":[92],"A":[93],"point":[95],"detector":[96],"work":[101],"focusing":[102],"on":[103],"improving":[104],"handle":[109],"real-world":[110],"scenarios.":[111],"Various":[112],"trackers":[113,213],"models":[116,208],"tested":[118],"develop":[120],"algorithm":[123],"that":[124,158],"can":[125],"determine":[126],"collision":[128],"between":[129],"glove":[131,228,251],"torso":[134],"scenario.":[138],"We":[139],"conducted":[140],"several":[141],"experiments":[142],"using":[143],"CSRT":[144,169],"Boosting":[146,181],"trackers,":[147],"Mask":[149,160],"R-CNN":[150,161],"YoloV3":[152,177],"models.":[154],"It":[155],"shown":[157],"when":[159,176,239],"employed":[163],"as":[164],"model,":[167],"tracker":[170,182],"outperforms":[171],"other":[173],"trackers.":[174],"Conversely,":[175],"utilized,":[179],"yields":[183],"best":[185,212],"results.":[186],"When":[187,230],"assessing":[188],"hit":[189,244],"performance,":[191],"there":[192],"two":[194,207,232],"variables":[195],"consider,":[197],"namely,":[198],"viewpoints":[199],"speed":[201],"of":[202,220],"gloves.":[204],"Testing":[205],"with":[209],"corresponding":[211],"resulted":[214],"minimum":[217],"accuracy":[218,235],"rate":[219],"70%":[221],"single":[224],"viewpoint":[225,247],"slow":[227,250],"speed.":[229,252],"incorporating":[231],"viewpoints,":[233],"increases":[236],"90%":[238],"taking":[240],"into":[241],"account":[242],"either":[246],"at":[248]},"counts_by_year":[],"updated_date":"2026-03-29T06:01:01.467347","created_date":"2026-03-28T00:00:00"}