{"id":"https://openalex.org/W4205688110","doi":"https://doi.org/10.1109/ist50367.2021.9651400","title":"General-purpose Abandoned Object Detection Method without Background Modeling","display_name":"General-purpose Abandoned Object Detection Method without Background Modeling","publication_year":2021,"publication_date":"2021-08-24","ids":{"openalex":"https://openalex.org/W4205688110","doi":"https://doi.org/10.1109/ist50367.2021.9651400"},"language":"en","primary_location":{"id":"doi:10.1109/ist50367.2021.9651400","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ist50367.2021.9651400","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Imaging Systems and Techniques (IST)","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/A5100355623","display_name":"Weiping Liu","orcid":"https://orcid.org/0000-0002-9028-6369"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weiping Liu","raw_affiliation_strings":["North China Electric Power University,Yangzhong Intelligent Electrical Research Center,Yangzhong,China","Yangzhong Intelligent Electrical Research Center, North China Electric Power University, Yangzhong, China"],"affiliations":[{"raw_affiliation_string":"North China Electric Power University,Yangzhong Intelligent Electrical Research Center,Yangzhong,China","institution_ids":["https://openalex.org/I153473198"]},{"raw_affiliation_string":"Yangzhong Intelligent Electrical Research Center, North China Electric Power University, Yangzhong, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101734165","display_name":"Peng Liu","orcid":"https://orcid.org/0000-0003-1833-495X"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Liu","raw_affiliation_strings":["North China Electric Power University,Yangzhong Intelligent Electrical Research Center,Yangzhong,China","Yangzhong Intelligent Electrical Research Center, North China Electric Power University, Yangzhong, China"],"affiliations":[{"raw_affiliation_string":"North China Electric Power University,Yangzhong Intelligent Electrical Research Center,Yangzhong,China","institution_ids":["https://openalex.org/I153473198"]},{"raw_affiliation_string":"Yangzhong Intelligent Electrical Research Center, North China Electric Power University, Yangzhong, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062892790","display_name":"Chuanxin Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuanxin Xiao","raw_affiliation_strings":["North China Electric Power University,Yangzhong Intelligent Electrical Research Center,Yangzhong,China","Yangzhong Intelligent Electrical Research Center, North China Electric Power University, Yangzhong, China"],"affiliations":[{"raw_affiliation_string":"North China Electric Power University,Yangzhong Intelligent Electrical Research Center,Yangzhong,China","institution_ids":["https://openalex.org/I153473198"]},{"raw_affiliation_string":"Yangzhong Intelligent Electrical Research Center, North China Electric Power University, Yangzhong, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000692450","display_name":"Ruitong Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruitong Hu","raw_affiliation_strings":["North China Electric Power University,Yangzhong Intelligent Electrical Research Center,Yangzhong,China","Yangzhong Intelligent Electrical Research Center, North China Electric Power University, Yangzhong, China"],"affiliations":[{"raw_affiliation_string":"North China Electric Power University,Yangzhong Intelligent Electrical Research Center,Yangzhong,China","institution_ids":["https://openalex.org/I153473198"]},{"raw_affiliation_string":"Yangzhong Intelligent Electrical Research Center, North China Electric Power University, Yangzhong, China","institution_ids":["https://openalex.org/I153473198"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100355623"],"corresponding_institution_ids":["https://openalex.org/I153473198"],"apc_list":null,"apc_paid":null,"fwci":0.2913,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.5803606,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"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":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/T10036","display_name":"Advanced Neural Network Applications","score":0.9984999895095825,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9979000091552734,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7876379489898682},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7722218036651611},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.7426197528839111},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.741737961769104},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6208752989768982},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5740746259689331},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5440948605537415},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.5170710682868958},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.5052247643470764},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.4636451303958893},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.43918728828430176},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42735564708709717},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.28002282977104187},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.13359975814819336},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09521299600601196}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7876379489898682},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7722218036651611},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7426197528839111},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.741737961769104},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6208752989768982},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5740746259689331},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5440948605537415},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.5170710682868958},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.5052247643470764},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.4636451303958893},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.43918728828430176},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42735564708709717},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28002282977104187},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.13359975814819336},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09521299600601196},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ist50367.2021.9651400","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ist50367.2021.9651400","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Imaging Systems and Techniques (IST)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.5799999833106995,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1992925827","https://openalex.org/W2029757057","https://openalex.org/W2079781220","https://openalex.org/W2102625004","https://openalex.org/W2127070222","https://openalex.org/W2518246700","https://openalex.org/W2863506664","https://openalex.org/W2897680579","https://openalex.org/W2905522107","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W3043680005","https://openalex.org/W3106250896","https://openalex.org/W3118407707","https://openalex.org/W6620707391","https://openalex.org/W6628973269","https://openalex.org/W6670824115","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2972620127","https://openalex.org/W2981141433","https://openalex.org/W2802018156","https://openalex.org/W4313315626","https://openalex.org/W2949096641","https://openalex.org/W2101531944","https://openalex.org/W2970686063","https://openalex.org/W4320729701","https://openalex.org/W2922437833","https://openalex.org/W2100052226"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"an":[3],"effective":[4,87],"method":[5,66,85],"for":[6,88],"detecting":[7,89],"abandoned":[8,57,63,90],"objects":[9,91],"in":[10],"surveillance":[11,26],"videos.":[12,27],"We":[13],"use":[14,70],"a":[15,61],"pedestrian":[16],"detector":[17],"trained":[18],"by":[19],"YOLO":[20],"deep":[21],"learning":[22],"model":[23],"to":[24,52,96],"detect":[25],"In":[28],"this":[29,84],"process,":[30],"key":[31,50],"frames":[32,51],"before":[33],"and":[34,47,92],"after":[35],"pedestrians":[36],"pass":[37],"through":[38],"the":[39,49,54,79,100],"scene":[40],"can":[41],"be":[42],"obtained.":[43],"Subsequently,":[44],"we":[45],"compare":[46],"analyze":[48],"get":[53],"position":[55],"of":[56],"objects.":[58],"It":[59],"is":[60,86,93],"general-purpose":[62],"object":[64],"detection":[65],"that":[67,83],"does":[68],"not":[69],"background":[71,104],"modeling.":[72,105],"The":[73],"experimental":[74],"results":[75],"obtained":[76],"based":[77],"on":[78],"ABODA":[80],"database":[81],"show":[82],"more":[94],"robust":[95],"illumination":[97],"changes":[98],"than":[99],"common":[101],"methods":[102],"using":[103]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-04-11T08:14:18.477133","created_date":"2025-10-10T00:00:00"}
