{"id":"https://openalex.org/W4210896196","doi":"https://doi.org/10.1109/tsmc.2022.3146455","title":"Bayesian Modeling of Crowd Dynamics by Aggregating Multiresolution Observations From UAVs and UGVs","display_name":"Bayesian Modeling of Crowd Dynamics by Aggregating Multiresolution Observations From UAVs and UGVs","publication_year":2022,"publication_date":"2022-02-07","ids":{"openalex":"https://openalex.org/W4210896196","doi":"https://doi.org/10.1109/tsmc.2022.3146455"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmc.2022.3146455","pdf_url":null,"source":{"id":"https://openalex.org/S4210209078","display_name":"IEEE Transactions on Systems Man and Cybernetics Systems","issn_l":"2168-2216","issn":["2168-2216","2168-2232"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"journal-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/A5101708283","display_name":"Yifei Yuan","orcid":"https://orcid.org/0000-0002-9089-580X"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yifei Yuan","raw_affiliation_strings":["Department of Systems and Industrial Engineering, University of Arizona, Tucson, AZ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Systems and Industrial Engineering, University of Arizona, Tucson, AZ, USA","institution_ids":["https://openalex.org/I138006243"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021741380","display_name":"Young\u2010Jun Son","orcid":"https://orcid.org/0000-0002-4004-2155"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Young-Jun Son","raw_affiliation_strings":["Department of Systems and Industrial Engineering, University of Arizona, Tucson, AZ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Systems and Industrial Engineering, University of Arizona, Tucson, AZ, USA","institution_ids":["https://openalex.org/I138006243"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100414715","display_name":"Jian Liu","orcid":"https://orcid.org/0000-0003-0268-2941"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jian Liu","raw_affiliation_strings":["Department of Systems and Industrial Engineering, University of Arizona, Tucson, AZ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Systems and Industrial Engineering, University of Arizona, Tucson, AZ, USA","institution_ids":["https://openalex.org/I138006243"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.544,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.999942,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":77,"max":81},"biblio":{"volume":"52","issue":"10","first_page":"6406","last_page":"6417"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Visual Object Tracking and Person Re-identification","score":0.9994,"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":"Visual Object Tracking and Person Re-identification","score":0.9994,"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/T11133","display_name":"Unmanned Aerial Vehicle Communications","score":0.9969,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11500","display_name":"Modeling Pedestrian Dynamics and Evacuations","score":0.9954,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/robustness","display_name":"Robustness (evolution)","score":0.63563377},{"id":"https://openalex.org/keywords/crowd-simulation","display_name":"Crowd Simulation","score":0.572816},{"id":"https://openalex.org/keywords/multiple-object-tracking","display_name":"Multiple Object Tracking","score":0.562911},{"id":"https://openalex.org/keywords/crowd-behavior","display_name":"Crowd Behavior","score":0.546461},{"id":"https://openalex.org/keywords/visual-tracking","display_name":"Visual Tracking","score":0.544054},{"id":"https://openalex.org/keywords/motion-detection","display_name":"Motion Detection","score":0.536334}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.73648816},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.63563377},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5381734},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5137087},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5119692},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48327544},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40287358},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34508246},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmc.2022.3146455","pdf_url":null,"source":{"id":"https://openalex.org/S4210209078","display_name":"IEEE Transactions on Systems Man and Cybernetics Systems","issn_l":"2168-2216","issn":["2168-2216","2168-2232"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[{"funder":"https://openalex.org/F4320338279","funder_display_name":"Air Force Office of Scientific Research","award_id":"FA9550-17-1-0075"},{"funder":"https://openalex.org/F4320338279","funder_display_name":"Air Force Office of Scientific Research","award_id":"FA9550-12-1-0238"}],"datasets":[],"versions":[],"referenced_works_count":45,"referenced_works":["https://openalex.org/W1767829066","https://openalex.org/W1968149994","https://openalex.org/W1984505032","https://openalex.org/W1987118352","https://openalex.org/W1990822420","https://openalex.org/W1996920238","https://openalex.org/W2000456104","https://openalex.org/W2012929209","https://openalex.org/W2017056417","https://openalex.org/W2033049381","https://openalex.org/W2037095848","https://openalex.org/W2039430607","https://openalex.org/W2048290715","https://openalex.org/W2065994824","https://openalex.org/W2071325740","https://openalex.org/W2086807667","https://openalex.org/W2104969271","https://openalex.org/W2135347708","https://openalex.org/W2147481900","https://openalex.org/W2175800718","https://openalex.org/W2343678873","https://openalex.org/W2561025508","https://openalex.org/W2726842553","https://openalex.org/W2767906581","https://openalex.org/W2788817046","https://openalex.org/W2792016338","https://openalex.org/W2800626432","https://openalex.org/W2803437104","https://openalex.org/W2898707792","https://openalex.org/W2942012181","https://openalex.org/W2962703917","https://openalex.org/W2984966510","https://openalex.org/W3036052146","https://openalex.org/W3036246869","https://openalex.org/W3045180775","https://openalex.org/W3094093649","https://openalex.org/W3095686063","https://openalex.org/W3099129097","https://openalex.org/W3111286166","https://openalex.org/W3113075130","https://openalex.org/W3128513362","https://openalex.org/W3133161538","https://openalex.org/W3164593594","https://openalex.org/W3217285792","https://openalex.org/W4213147678"],"related_works":["https://openalex.org/W4303857162","https://openalex.org/W4288266653","https://openalex.org/W3015855446","https://openalex.org/W2969189870","https://openalex.org/W2965643117","https://openalex.org/W2950975704","https://openalex.org/W2585791450","https://openalex.org/W2505726097","https://openalex.org/W2407375987","https://openalex.org/W2372267530"],"abstract_inverted_index":{"Unmanned":[0],"aerial":[1],"vehicles":[2,7],"(UAVs)":[3],"and":[4,33,77,87,113,127,157,163,172],"unmanned":[5],"ground":[6],"(UGVs)":[8],"can":[9],"be":[10],"jointly":[11],"deployed":[12],"to":[13,28,52,102,119,144,168],"form":[14],"a":[15,25,30,39,71,81,96,108,137],"collaborative":[16],"surveillance":[17],"system,":[18],"where":[19,153],"UAVs":[20],"collect":[21],"low-resolution":[22,124],"images":[23,37],"at":[24],"high":[26,154],"altitude":[27],"obtain":[29],"global":[31],"perception":[32],"UGVs":[34],"observe":[35],"high-resolution":[36,128],"within":[38],"focused":[40],"detection":[41],"range.":[42],"Such":[43],"multiresolution":[44,64,105],"heterogeneous":[45],"observations":[46,65,126],"create":[47],"opportunities":[48],"yet":[49],"pose":[50],"challenges":[51],"model":[53,120,139],"the":[54,57,104,134,170,175],"dynamics":[55,99,122,151],"of":[56,70,74,83,174],"targeted":[58],"crowds.":[59],"Existing":[60],"approaches":[61],"that":[62],"integrate":[63],"rely":[66],"on":[67,133],"intensive":[68],"computation":[69],"large":[72],"volume":[73],"historical":[75],"data,":[76],"thus,":[78],"result":[79],"in":[80],"lack":[82],"computational":[84],"efficiency,":[85,155],"accuracy,":[86,156],"robustness.":[88],"To":[89],"address":[90],"these":[91],"limitations,":[92],"this":[93],"article":[94],"proposes":[95],"new":[97],"crowd":[98,121,150],"modeling":[100,177],"approach":[101],"aggregating":[103],"information":[106,146],"under":[107],"Bayesian":[109],"inference":[110],"framework.":[111],"Beta-binomial":[112],"Normal\u2013Wishart":[114],"conjugate":[115],"distributions":[116],"were":[117,166],"adopted":[118],"from":[123],"UAV":[125],"UGV":[129],"observations,":[130],"respectively.":[131],"Based":[132],"proposed":[135,176],"approach,":[136],"real-time":[138],"updating":[140],"mechanism":[141],"is":[142],"developed":[143],"implement":[145],"aggregation":[147],"for":[148],"onboard":[149,164],"inference,":[152],"robustness":[158],"are":[159],"critical.":[160],"Numerical":[161],"simulations":[162],"experiments":[165],"conducted":[167],"demonstrate":[169],"effectiveness":[171],"efficiency":[173],"approach.":[178]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4210896196","counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2024-10-29T01:02:34.320053","created_date":"2022-02-09"}
