{"id":"https://openalex.org/W4286277823","doi":"https://doi.org/10.1109/ist55454.2022.9827759","title":"Unsupervised Anomaly Detection in Traffic Surveillance Based on Global Foreground Modeling","display_name":"Unsupervised Anomaly Detection in Traffic Surveillance Based on Global Foreground Modeling","publication_year":2022,"publication_date":"2022-06-21","ids":{"openalex":"https://openalex.org/W4286277823","doi":"https://doi.org/10.1109/ist55454.2022.9827759"},"language":"en","primary_location":{"id":"doi:10.1109/ist55454.2022.9827759","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ist55454.2022.9827759","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Imaging Systems and Techniques (IST)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5041683820","display_name":"Hang Shi","orcid":"https://orcid.org/0000-0002-6326-9942"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hang Shi","raw_affiliation_strings":["Innovative AI Technologies,Newark,NJ,USA,07103"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Innovative AI Technologies,Newark,NJ,USA,07103","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014533739","display_name":"Hadi Ghahremannezhad","orcid":"https://orcid.org/0000-0003-2795-4464"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hadi Ghahremannezhad","raw_affiliation_strings":["New Jersey Institute of Technology,Department of Computer Science,Newark,NJ,USA,07102"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New Jersey Institute of Technology,Department of Computer Science,Newark,NJ,USA,07102","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100454866","display_name":"Chengjun Liu","orcid":"https://orcid.org/0000-0002-2036-0770"},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chengjun Liu","raw_affiliation_strings":["New Jersey Institute of Technology,Department of Computer Science,Newark,NJ,USA,07102"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New Jersey Institute of Technology,Department of Computer Science,Newark,NJ,USA,07102","institution_ids":["https://openalex.org/I118118575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":null,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":1.0,"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":1.0,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T12597","display_name":"Fire Detection and Safety Systems","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/background-subtraction","display_name":"Background subtraction","score":0.9132795333862305},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8011617064476013},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7288185954093933},{"id":"https://openalex.org/keywords/foreground-detection","display_name":"Foreground detection","score":0.6889243721961975},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.672805905342102},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5648177862167358},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5479812026023865},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.45707541704177856},{"id":"https://openalex.org/keywords/background-image","display_name":"Background image","score":0.4126265347003937},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3561892509460449},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.20762720704078674},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1718587577342987}],"concepts":[{"id":"https://openalex.org/C32653426","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Background subtraction","level":3,"score":0.9132795333862305},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8011617064476013},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7288185954093933},{"id":"https://openalex.org/C2779769447","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Foreground detection","level":4,"score":0.6889243721961975},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.672805905342102},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5648177862167358},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5479812026023865},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.45707541704177856},{"id":"https://openalex.org/C3019635856","wikidata":"https://www.wikidata.org/wiki/Q1619726","display_name":"Background image","level":3,"score":0.4126265347003937},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3561892509460449},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.20762720704078674},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1718587577342987}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ist55454.2022.9827759","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ist55454.2022.9827759","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Imaging Systems and Techniques (IST)","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":30,"referenced_works":["https://openalex.org/W1969977005","https://openalex.org/W2035866593","https://openalex.org/W2069057506","https://openalex.org/W2071860582","https://openalex.org/W2102625004","https://openalex.org/W2111861511","https://openalex.org/W2112076978","https://openalex.org/W2171885832","https://openalex.org/W2507402573","https://openalex.org/W2525668722","https://openalex.org/W2759692151","https://openalex.org/W2783946051","https://openalex.org/W2817412859","https://openalex.org/W2888845200","https://openalex.org/W2894396292","https://openalex.org/W2903256124","https://openalex.org/W3039606655","https://openalex.org/W3097325428","https://openalex.org/W3129045723","https://openalex.org/W3129790038","https://openalex.org/W3171734802","https://openalex.org/W3201095160","https://openalex.org/W3208316687","https://openalex.org/W4205374438","https://openalex.org/W4237743494","https://openalex.org/W4248936881","https://openalex.org/W4250533120","https://openalex.org/W4298266977","https://openalex.org/W6676769703","https://openalex.org/W6752722560"],"related_works":["https://openalex.org/W2123129869","https://openalex.org/W2188430267","https://openalex.org/W4309442235","https://openalex.org/W4226212444","https://openalex.org/W3138277141","https://openalex.org/W2055234710","https://openalex.org/W2979792331","https://openalex.org/W1976932551","https://openalex.org/W2074454122","https://openalex.org/W1987287817"],"abstract_inverted_index":{"One":[0],"of":[1,12,19,43,77,84,173,191],"the":[2,10,16,20,51,57,64,71,75,85,102,107,110,116,132,137,142,153,158,171,174,182,187,196],"main":[3,82],"challenges":[4],"facing":[5],"foreground":[6,33,46,61,112,138,144,208],"detection":[7,18,139],"methods":[8],"in":[9,214],"applications":[11],"video":[13],"analytic,":[14],"is":[15,41,48,97,150,203],"continuous":[17],"objects":[21],"after":[22],"they":[23],"have":[24],"stopped":[25,45,60,143,207,212],"moving.":[26],"In":[27,177],"this":[28],"paper,":[29],"a":[30,90,120,130,147],"novel":[31,91],"global":[32],"modeling":[34,66,95,122,201],"(GFM)":[35],"guided":[36,93,199],"background":[37,65,79,94,103,121,200],"subtraction":[38],"method,":[39,53,67,123,127],"which":[40,54,68],"capable":[42],"detecting":[44],"objects,":[47,62,73,209],"presented.":[49],"Specifically,":[50],"GFM":[52,92,117,198],"detects":[55,69,141],"both":[56,135],"moving":[58,72],"and":[59,119,140],"guides":[63],"only":[70],"for":[74,156],"purpose":[76],"adaptive":[78],"updating.":[80],"The":[81],"contributions":[83],"paper":[86],"are":[87,167],"two-fold.":[88],"First,":[89],"method":[96,118,134,155,202],"proposed":[98,133,154,175,197],"by":[99,115,162],"adaptively":[100],"updating":[101],"model":[104],"based":[105],"on":[106],"differences":[108],"between":[109],"two":[111],"masks":[113],"produced":[114],"such":[124,210],"as":[125,211],"Zivkovic's":[126],"respectively.":[128],"As":[129],"result,":[131],"improves":[136],"objects.":[145],"Second,":[146],"boosting":[148],"strategy":[149],"integrated":[151],"into":[152],"eliminating":[157],"false":[159],"alarms":[160],"caused":[161],"noise.":[163],"Real":[164],"traffic":[165,184],"videos":[166,185],"used":[168],"to":[169,205],"evaluate":[170],"effectiveness":[172],"method.":[176],"particular,":[178],"experimental":[179],"results":[180],"using":[181],"real":[183,215],"from":[186],"New":[188],"Jersey":[189],"Department":[190],"Transportation":[192],"(NJDOT)":[193],"show":[194],"that":[195],"able":[204],"detect":[206],"vehicles,":[213],"time.":[216]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}