{"id":"https://openalex.org/W3210339021","doi":"https://doi.org/10.1109/ccece53047.2021.9569159","title":"GroupNet: Detecting the Social Distancing Violation using Object Tracking in Crowdscene","display_name":"GroupNet: Detecting the Social Distancing Violation using Object Tracking in Crowdscene","publication_year":2021,"publication_date":"2021-09-12","ids":{"openalex":"https://openalex.org/W3210339021","doi":"https://doi.org/10.1109/ccece53047.2021.9569159","mag":"3210339021"},"language":"en","primary_location":{"id":"doi:10.1109/ccece53047.2021.9569159","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccece53047.2021.9569159","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","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/A5110683407","display_name":"Anthony Boyko","orcid":null},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]},{"id":"https://openalex.org/I4405260628","display_name":"University of British Columbia, Okanagan Campus","ror":"https://ror.org/04241wz75","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490","https://openalex.org/I4405260628"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Anthony Boyko","raw_affiliation_strings":["Department of Computer Science, Mathematics, Physics and Statistics, University of British Columbia, Kelowna, BC, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Mathematics, Physics and Statistics, University of British Columbia, Kelowna, BC, Canada","institution_ids":["https://openalex.org/I141945490","https://openalex.org/I4405260628"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048871510","display_name":"Mohamed H. Abdelpakey","orcid":"https://orcid.org/0000-0002-4753-8380"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]},{"id":"https://openalex.org/I4405260628","display_name":"University of British Columbia, Okanagan Campus","ror":"https://ror.org/04241wz75","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490","https://openalex.org/I4405260628"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mohamed H. Abdelpakey","raw_affiliation_strings":["Department of Computer Science, Mathematics, Physics and Statistics, University of British Columbia, Kelowna, BC, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Mathematics, Physics and Statistics, University of British Columbia, Kelowna, BC, Canada","institution_ids":["https://openalex.org/I141945490","https://openalex.org/I4405260628"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085128370","display_name":"Mohamed Shehata","orcid":"https://orcid.org/0000-0002-8464-8650"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]},{"id":"https://openalex.org/I4405260628","display_name":"University of British Columbia, Okanagan Campus","ror":"https://ror.org/04241wz75","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490","https://openalex.org/I4405260628"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mohamed S. Shehata","raw_affiliation_strings":["Department of Computer Science, Mathematics, Physics and Statistics, University of British Columbia, Kelowna, BC, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Mathematics, Physics and Statistics, University of British Columbia, Kelowna, BC, Canada","institution_ids":["https://openalex.org/I141945490","https://openalex.org/I4405260628"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5110683407"],"corresponding_institution_ids":["https://openalex.org/I141945490","https://openalex.org/I4405260628"],"apc_list":null,"apc_paid":null,"fwci":0.0969,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.41473534,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994999766349792,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994999766349792,"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/T10410","display_name":"COVID-19 epidemiological studies","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2611","display_name":"Modeling and Simulation"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/social-distance","display_name":"Social distance","score":0.8073741793632507},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.572501540184021},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5651606917381287},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5491105914115906},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5426942706108093},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.49894070625305176},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.49107861518859863},{"id":"https://openalex.org/keywords/distance-matrix","display_name":"Distance matrix","score":0.45262664556503296},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.4237670302391052},{"id":"https://openalex.org/keywords/group","display_name":"Group (periodic table)","score":0.4201950430870056},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3350939154624939},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2052920162677765}],"concepts":[{"id":"https://openalex.org/C172656115","wikidata":"https://www.wikidata.org/wiki/Q2142613","display_name":"Social distance","level":5,"score":0.8073741793632507},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.572501540184021},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5651606917381287},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5491105914115906},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5426942706108093},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.49894070625305176},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.49107861518859863},{"id":"https://openalex.org/C111208986","wikidata":"https://www.wikidata.org/wiki/Q901698","display_name":"Distance matrix","level":2,"score":0.45262664556503296},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.4237670302391052},{"id":"https://openalex.org/C2781311116","wikidata":"https://www.wikidata.org/wiki/Q83306","display_name":"Group (periodic table)","level":2,"score":0.4201950430870056},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3350939154624939},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2052920162677765},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","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/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.0},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.0},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccece53047.2021.9569159","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccece53047.2021.9569159","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6899999976158142,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1677182931","https://openalex.org/W2042015300","https://openalex.org/W2061773916","https://openalex.org/W2152945944","https://openalex.org/W2171243491","https://openalex.org/W2508962983","https://openalex.org/W2555751471","https://openalex.org/W2796347433","https://openalex.org/W2952819818","https://openalex.org/W2962677013","https://openalex.org/W2962923976","https://openalex.org/W2963037989","https://openalex.org/W2978171022","https://openalex.org/W2986732333","https://openalex.org/W3033201346","https://openalex.org/W3038660445","https://openalex.org/W3095178570","https://openalex.org/W3106763294","https://openalex.org/W3118212025","https://openalex.org/W3177587866","https://openalex.org/W4293584584","https://openalex.org/W6620707391","https://openalex.org/W6697005757","https://openalex.org/W6730410022","https://openalex.org/W6750227808"],"related_works":["https://openalex.org/W1605858995","https://openalex.org/W2908582041","https://openalex.org/W4294328694","https://openalex.org/W2977833894","https://openalex.org/W2908357282","https://openalex.org/W2119897186","https://openalex.org/W2095428304","https://openalex.org/W1997141628","https://openalex.org/W2348550256","https://openalex.org/W4366087900"],"abstract_inverted_index":{"COVID-19":[0],"affects":[1],"everyone":[2],"on":[3],"a":[4,60,100,119,128,144,159,163,167],"daily-basis":[5],"causing":[6],"adjustments":[7,16],"in":[8,85,207,249,252],"which":[9],"society":[10],"functions.":[11],"One":[12],"of":[13,71,78,104,171,204,221,228,235,255,265],"these":[14],"major":[15],"is":[17,30,148,210,223],"the":[18,48,69,76,90,109,140,151,193,205,233,243,250,253,263],"need":[19],"to":[20,32,38,50,74,139,178,190,232,258],"measure":[21],"how":[22],"well":[23],"people":[24],"distance":[25,52,103,182,195,209],"from":[26,136,166],"each":[27,184],"other,":[28],"that":[29,81],"referred":[31],"as":[33,127],"social":[34,40,64,91],"distancing.":[35],"Previous":[36],"work":[37],"automate":[39],"distancing":[41,65,92],"violations":[42],"does":[43],"not":[44],"take":[45],"into":[46],"consideration":[47],"exceptions":[49],"minimum":[51],"guidelines.":[53],"In":[54],"this":[55],"paper,":[56],"we":[57],"propose":[58],"GroupNet,":[59],"novel":[61],"multi-object":[62,125,168],"tracking":[63],"violation":[66,93],"detector":[67],"through":[68,161,242],"addition":[70,264],"group":[72,114,132,160,213,218,259],"detection":[73,260],"reduce":[75],"number":[77,254],"false":[79],"positives":[80],"are":[82,98,158,174],"currently":[83],"missed":[84],"existing":[86],"literature.":[87],"We":[88],"define":[89],"occurs":[94],"when":[95],"two":[96,105,156,197],"individuals":[97,157,180,198,216],"within":[99],"specified":[101],"Euclidean":[102],"meters.":[106],"GroupNet":[107,117,153,222,241],"leverages":[108],"contextual":[110],"information":[111],"learned":[112],"by":[113,225],"detection.":[115,133],"Moreover,":[116,240],"uses":[118,187],"Joint":[120],"Detection":[121],"and":[122],"Embedding":[123],"(JDE)":[124],"tracker":[126],"backbone":[129],"network":[130],"for":[131,150],"To":[134],"map":[135],"pixel-wise":[137],"coordinates":[138],"real-world":[141],"equivalent":[142],"coordinate,":[143],"pre-processed":[145],"affine":[146],"matrix":[147],"used":[149],"transformation.":[152],"determines":[154,212],"if":[155,192],"leveraging":[162],"re-identification":[164],"component":[165],"tracker.":[169],"Location":[170],"bounding":[172],"boxes":[173],"tracked":[175],"over":[176,200],"time":[177],"obtain":[179],"relative":[181,194,208],"between":[183,196,215],"other.":[185],"Group-Net":[186],"regression":[188],"analysis":[189,261],"determine":[191],"changes":[199],"time.":[201],"The":[202],"likelihood":[203],"change":[206],"non-zero":[211],"existence":[214],"(i.e.":[217],"detection).":[219],"Performance":[220],"evaluated":[224],"manual":[226],"inspection":[227],"output":[229],"images":[230],"due":[231,257],"lack":[234],"labeled":[236],"ground":[237],"truth":[238],"data.":[239],"provided":[244],"experiments":[245],"shows":[246],"an":[247],"improvement":[248],"reduction":[251],"false-positives":[256],"alongside":[262],"minimal":[266],"false-negatives.":[267]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}
