{"id":"https://openalex.org/W2071709758","doi":"https://doi.org/10.1109/robio.2013.6739583","title":"Robust abandoned object detection and analysis based on online learning","display_name":"Robust abandoned object detection and analysis based on online learning","publication_year":2013,"publication_date":"2013-12-01","ids":{"openalex":"https://openalex.org/W2071709758","doi":"https://doi.org/10.1109/robio.2013.6739583","mag":"2071709758"},"language":"en","primary_location":{"id":"doi:10.1109/robio.2013.6739583","is_oa":false,"landing_page_url":"https://doi.org/10.1109/robio.2013.6739583","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Robotics and Biomimetics (ROBIO)","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/A5102351820","display_name":"Lin Chang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Lin Chang","raw_affiliation_strings":["Shenzhen National Engineering Laboratory of Digital Television Co., Ltd","Shenzhen Nat. Eng. Lab., Digital Telev. Co., Ltd., Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen National Engineering Laboratory of Digital Television Co., Ltd","institution_ids":[]},{"raw_affiliation_string":"Shenzhen Nat. Eng. Lab., Digital Telev. Co., Ltd., Shenzhen, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101472952","display_name":"Hongmei Zhao","orcid":"https://orcid.org/0000-0002-5142-2516"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongmei Zhao","raw_affiliation_strings":["Engineering Lab on Intelligent Perception for Internet of Things(ELIP), Peking University, China","Eng. Lab. on Intell. Perception for Internet of Things (ELIP), Peking Univ., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Engineering Lab on Intelligent Perception for Internet of Things(ELIP), Peking University, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Eng. Lab. on Intell. Perception for Internet of Things (ELIP), Peking Univ., Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081387814","display_name":"Sen Zhai","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sen Zhai","raw_affiliation_strings":["Engineering Lab on Intelligent Perception for Internet of Things(ELIP), Peking University, China","Eng. Lab. on Intell. Perception for Internet of Things (ELIP), Peking Univ., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Engineering Lab on Intelligent Perception for Internet of Things(ELIP), Peking University, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Eng. Lab. on Intell. Perception for Internet of Things (ELIP), Peking Univ., Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054805114","display_name":"MA Ya-fei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yafei Ma","raw_affiliation_strings":["Shenzhen National Engineering Laboratory of Digital Television Co., Ltd","Shenzhen Nat. Eng. Lab., Digital Telev. Co., Ltd., Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen National Engineering Laboratory of Digital Television Co., Ltd","institution_ids":[]},{"raw_affiliation_string":"Shenzhen Nat. Eng. Lab., Digital Telev. Co., Ltd., Shenzhen, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100410352","display_name":"Hong Liu","orcid":"https://orcid.org/0000-0003-1640-9620"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Liu","raw_affiliation_strings":["Engineering Lab on Intelligent Perception for Internet of Things(ELIP), Peking University, China","Eng. Lab. on Intell. Perception for Internet of Things (ELIP), Peking Univ., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Engineering Lab on Intelligent Perception for Internet of Things(ELIP), Peking University, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Eng. Lab. on Intell. Perception for Internet of Things (ELIP), Peking Univ., Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5102351820"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.633,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.86271366,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"1","issue":null,"first_page":"940","last_page":"945"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9937000274658203,"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":0.9919999837875366,"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/computer-science","display_name":"Computer science","score":0.7817001342773438},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.7559402585029602},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7353625893592834},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6467868685722351},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5688656568527222},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5614456534385681},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4978160858154297},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.46661511063575745},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44089847803115845},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.4343153238296509},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.41788727045059204},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.2096526324748993}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7817001342773438},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7559402585029602},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7353625893592834},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6467868685722351},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5688656568527222},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5614456534385681},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4978160858154297},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.46661511063575745},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44089847803115845},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.4343153238296509},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.41788727045059204},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2096526324748993},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/robio.2013.6739583","is_oa":false,"landing_page_url":"https://doi.org/10.1109/robio.2013.6739583","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Robotics and Biomimetics (ROBIO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1996703663","https://openalex.org/W2012334287","https://openalex.org/W2056586066","https://openalex.org/W2081947144","https://openalex.org/W2098809774","https://openalex.org/W2102625004","https://openalex.org/W2111427798","https://openalex.org/W2121585324","https://openalex.org/W2122122769","https://openalex.org/W2122453363","https://openalex.org/W2140982548","https://openalex.org/W2143023146","https://openalex.org/W2164598857","https://openalex.org/W2167613050","https://openalex.org/W2170865122","https://openalex.org/W2171140863","https://openalex.org/W3145548334","https://openalex.org/W6676973682","https://openalex.org/W6678265996","https://openalex.org/W6792825239"],"related_works":["https://openalex.org/W2125652721","https://openalex.org/W1540371141","https://openalex.org/W4231274751","https://openalex.org/W1549363203","https://openalex.org/W2154063878","https://openalex.org/W2556012038","https://openalex.org/W1489772951","https://openalex.org/W1538046993","https://openalex.org/W2571255492","https://openalex.org/W2963610131"],"abstract_inverted_index":{"In":[0,190],"this":[1],"paper,":[2],"we":[3],"propose":[4],"a":[5,61,97,134,159,164,182],"novel":[6],"approach":[7],"based":[8,95,161,167],"on":[9,96,108],"online":[10,92,129,173],"learning":[11],"for":[12,23,100],"accurate":[13],"and":[14,87,102,119,150,187,197,206],"effective":[15],"detection":[16,26,59],"of":[17,33,37,158,185],"abandoned":[18,24,29,39,51,85,148],"objects.":[19],"Most":[20],"existing":[21],"methods":[22,42],"objects":[25,30,52,86,101,112,123,137,149],"only":[27],"detect":[28,84,147],"without":[31,75],"considering":[32],"the":[34,38,109,121,127,140,191,194,201],"logic":[35,117],"owner":[36,153],"object.":[40],"These":[41],"need":[43],"an":[44],"advanced":[45,77],"trained":[46,78],"human":[47,58,79],"detector":[48,80],"to":[49,83,146,179,181],"discriminate":[50],"from":[53],"still":[54],"persons":[55,103],"frequently.":[56],"However,":[57],"is":[60,81,94,170,177],"challenge":[62],"in":[63,104,126,139,154],"robotic":[64],"vision":[65],"system,":[66],"which":[67,142,176],"always":[68],"needs":[69],"off-line":[70],"training.":[71],"The":[72,91],"proposed":[73,202],"framework":[74,93],"specific":[76],"able":[82,178],"analyze":[88,151],"their":[89,116,152],"owners.":[90],"valid":[98],"assumption":[99],"natural":[105],"scenes.":[106],"Based":[107],"assumptions":[110],"that":[111],"are":[113,124,131],"moved":[114],"by":[115],"owners":[118],"all":[120],"moving":[122,136],"humans":[125],"scene,":[128,141],"classifiers":[130],"established":[132,171],"with":[133],"certain":[135],"just":[138],"can":[143],"assist":[144],"us":[145],"true":[155],"sense.":[156],"Instead":[157],"pixel":[160],"background":[162,168],"model,":[163],"robust":[165],"block":[166],"model":[169],"using":[172],"boosting":[174],"method,":[175],"adapt":[180],"large":[183],"variety":[184],"environment":[186],"complex":[188],"changes.":[189],"evaluation":[192],"over":[193],"PETS":[195],"2006":[196],"AVSS":[198],"2007":[199],"datasets,":[200],"technique":[203],"performs":[204],"robustly":[205],"efficiently.":[207]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}