{"id":"https://openalex.org/W4319660183","doi":"https://doi.org/10.1142/s0218001423540071","title":"A Social Distance Monitoring Method Based on Improved YOLOv4 for Surveillance Videos","display_name":"A Social Distance Monitoring Method Based on Improved YOLOv4 for Surveillance Videos","publication_year":2023,"publication_date":"2023-02-10","ids":{"openalex":"https://openalex.org/W4319660183","doi":"https://doi.org/10.1142/s0218001423540071"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001423540071","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1142/s0218001423540071","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-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/A5034636418","display_name":"Xingquan Cai","orcid":"https://orcid.org/0000-0003-4885-3312"},"institutions":[{"id":"https://openalex.org/I1456306","display_name":"North China University of Technology","ror":"https://ror.org/01nky7652","country_code":"CN","type":"education","lineage":["https://openalex.org/I1456306"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xingquan Cai","raw_affiliation_strings":["School of Information Science and Technology, North China University of Technology, Beijing 100144, P. R. China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, North China University of Technology, Beijing 100144, P. R. China","institution_ids":["https://openalex.org/I1456306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014466209","display_name":"Shun Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I1456306","display_name":"North China University of Technology","ror":"https://ror.org/01nky7652","country_code":"CN","type":"education","lineage":["https://openalex.org/I1456306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shun Zhou","raw_affiliation_strings":["School of Information Science and Technology, North China University of Technology, Beijing 100144, P. R. China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, North China University of Technology, Beijing 100144, P. R. China","institution_ids":["https://openalex.org/I1456306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103171518","display_name":"Pengyan Cheng","orcid":"https://orcid.org/0009-0009-6212-6382"},"institutions":[{"id":"https://openalex.org/I1456306","display_name":"North China University of Technology","ror":"https://ror.org/01nky7652","country_code":"CN","type":"education","lineage":["https://openalex.org/I1456306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengyan Cheng","raw_affiliation_strings":["School of Information Science and Technology, North China University of Technology, Beijing 100144, P. R. China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, North China University of Technology, Beijing 100144, P. R. China","institution_ids":["https://openalex.org/I1456306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112894374","display_name":"Dingwei Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I1456306","display_name":"North China University of Technology","ror":"https://ror.org/01nky7652","country_code":"CN","type":"education","lineage":["https://openalex.org/I1456306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dingwei Feng","raw_affiliation_strings":["School of Information Science and Technology, North China University of Technology, Beijing 100144, P. R. China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, North China University of Technology, Beijing 100144, P. R. China","institution_ids":["https://openalex.org/I1456306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100359479","display_name":"Haiyan Sun","orcid":"https://orcid.org/0000-0001-5498-8251"},"institutions":[{"id":"https://openalex.org/I1456306","display_name":"North China University of Technology","ror":"https://ror.org/01nky7652","country_code":"CN","type":"education","lineage":["https://openalex.org/I1456306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiyan Sun","raw_affiliation_strings":["School of Information Science and Technology, North China University of Technology, Beijing 100144, P. R. China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, North China University of Technology, Beijing 100144, P. R. China","institution_ids":["https://openalex.org/I1456306"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071195738","display_name":"Jiaqi Ji","orcid":"https://orcid.org/0000-0003-2693-1172"},"institutions":[{"id":"https://openalex.org/I94611258","display_name":"Hebei Normal University","ror":"https://ror.org/004rbbw49","country_code":"CN","type":"education","lineage":["https://openalex.org/I94611258"]},{"id":"https://openalex.org/I2800393352","display_name":"China Tourism Academy","ror":"https://ror.org/01k4abj61","country_code":"CN","type":"government","lineage":["https://openalex.org/I2800393352"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiaqi Ji","raw_affiliation_strings":["School of Mathematics and Computer Science, Hebei Normal University for Nationalities, Chengde 067000, P. R. China","The Technology Innovation Center of Cultural Tourism, Big Data of Hebei Province, Chengde 067000, P. R. China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Computer Science, Hebei Normal University for Nationalities, Chengde 067000, P. R. China","institution_ids":["https://openalex.org/I94611258"]},{"raw_affiliation_string":"The Technology Innovation Center of Cultural Tourism, Big Data of Hebei Province, Chengde 067000, P. R. China","institution_ids":["https://openalex.org/I2800393352"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5034636418","https://openalex.org/A5071195738"],"corresponding_institution_ids":["https://openalex.org/I1456306","https://openalex.org/I2800393352","https://openalex.org/I94611258"],"apc_list":null,"apc_paid":null,"fwci":0.2674,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.5043968,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"37","issue":"05","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13918","display_name":"Advanced Data and IoT Technologies","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13918","display_name":"Advanced Data and IoT Technologies","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9909999966621399,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.984499990940094,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7888354063034058},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6796801090240479},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.6417123079299927},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6232156157493591},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5808905363082886},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4620356857776642},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.45489591360092163},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42320680618286133},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3892483711242676},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33950161933898926},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11131742596626282},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09883549809455872}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7888354063034058},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6796801090240479},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.6417123079299927},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6232156157493591},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5808905363082886},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4620356857776642},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.45489591360092163},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42320680618286133},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3892483711242676},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33950161933898926},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11131742596626282},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09883549809455872},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","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},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218001423540071","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1142/s0218001423540071","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.44999998807907104,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2193819129","https://openalex.org/W2268622754","https://openalex.org/W2343818649","https://openalex.org/W2766084402","https://openalex.org/W2800806089","https://openalex.org/W2912371381","https://openalex.org/W2949631125","https://openalex.org/W2953735756","https://openalex.org/W3016819671","https://openalex.org/W3045368143","https://openalex.org/W3080965489","https://openalex.org/W3090437903","https://openalex.org/W3097072081","https://openalex.org/W3097720782","https://openalex.org/W3101454826","https://openalex.org/W3107249883","https://openalex.org/W3134751135","https://openalex.org/W3175566952","https://openalex.org/W3179749401","https://openalex.org/W4213381517","https://openalex.org/W4231970258","https://openalex.org/W4232827924","https://openalex.org/W4281478935","https://openalex.org/W4282829178"],"related_works":["https://openalex.org/W2392100589","https://openalex.org/W2512789322","https://openalex.org/W3122828758","https://openalex.org/W2101960027","https://openalex.org/W2197846993","https://openalex.org/W1976827262","https://openalex.org/W49697837","https://openalex.org/W2170799233","https://openalex.org/W2768112316","https://openalex.org/W4205958986"],"abstract_inverted_index":{"Social":[0],"distance":[1,24,39,120,127,138,187],"monitoring":[2,18,40,128,139,188],"is":[3],"of":[4,13,27,129,189],"great":[5],"significance":[6],"for":[7],"public":[8],"health":[9],"in":[10,25,151],"the":[11,60,65,71,78,89,100,105,111,117,124,135,155,164,173,184],"era":[12],"COVID-19":[14],"pandemic.":[15],"However,":[16],"existing":[17],"methods":[19],"cannot":[20],"effectively":[21],"detect":[22,147],"social":[23,38,126,137,186],"terms":[26],"efficiency,":[28],"accuracy,":[29],"and":[30,52,63,87,109,158],"robustness.":[31],"In":[32],"this":[33],"paper,":[34],"we":[35],"proposed":[36,136],"a":[37,54,82],"method":[41,50,58,76,98,140,170],"based":[42,69,115,141],"on":[43,70,116,142],"an":[44],"improved":[45,84,143,159],"YOLOv4":[46,85,144],"algorithm.":[47],"Specifically,":[48],"our":[49,57,75,97],"constructs":[51],"pre-processes":[53],"dataset.":[55],"Afterwards,":[56],"screens":[59],"valid":[61],"samples":[62],"improves":[64],"K-means":[66,160],"clustering":[67],"algorithm":[68,86,161],"IoU":[72],"distance.":[73],"Then,":[74],"detects":[77],"target":[79,91,149,166],"pedestrians":[80],"using":[81],"trained":[83],"gets":[88],"pedestrian":[90,125,148,165,185],"detection":[92,167],"frame":[93],"location":[94],"information.":[95],"Finally,":[96],"defines":[99],"observation":[101],"depth":[102],"parameters,":[103],"generates":[104],"3D":[106],"feature":[107],"space,":[108],"clusters":[110],"offending":[112,174],"aggregation":[113],"groups":[114,175],"L2":[118],"parametric":[119],"to":[121,182],"finally":[122],"realize":[123,183],"2D":[130,190],"video.":[131],"Experiments":[132],"show":[133],"that":[134],"can":[145,162,171],"accurately":[146],"locations":[150],"video":[152],"images,":[153],"where":[154],"pre-processing":[156],"operation":[157],"improve":[163],"accuracy.":[168],"Our":[169],"cluster":[172],"without":[176],"going":[177],"through":[178],"calibration":[179],"mapping":[180],"transformation":[181],"videos.":[191]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-12-24T23:09:58.560324","created_date":"2025-10-10T00:00:00"}
