{"id":"https://openalex.org/W2074800113","doi":"https://doi.org/10.1109/tcsvt.2013.2248239","title":"Selective Eigenbackground for Background Modeling and Subtraction in Crowded Scenes","display_name":"Selective Eigenbackground for Background Modeling and Subtraction in Crowded Scenes","publication_year":2013,"publication_date":"2013-02-23","ids":{"openalex":"https://openalex.org/W2074800113","doi":"https://doi.org/10.1109/tcsvt.2013.2248239","mag":"2074800113"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2013.2248239","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2013.2248239","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Circuits and Systems for Video Technology","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/A5023918894","display_name":"Yonghong Tian","orcid":"https://orcid.org/0000-0002-2978-5935"},"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":"Yonghong Tian","raw_affiliation_strings":["Peking University, School of Electrical Engineering and Computer Science, Beijing, China","[Sch. of Electr. Eng. & Comput. Sci., Peking Univ., Beijing, China]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University, School of Electrical Engineering and Computer Science, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"[Sch. of Electr. Eng. & Comput. Sci., Peking Univ., Beijing, China]","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100631216","display_name":"Yaowei Wang","orcid":"https://orcid.org/0000-0003-2197-9038"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaowei Wang","raw_affiliation_strings":["Department of Electronic Engineering, Beijing Institute of Technology, Beijing, China","Dept. of Electron. Eng., Beijing Inst. of Technol., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"Dept. of Electron. Eng., Beijing Inst. of Technol., Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112113390","display_name":"Zhipeng Hu","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":"Zhipeng Hu","raw_affiliation_strings":["Peking University, School of Electrical Engineering and Computer Science, Beijing, China","[Sch. of Electr. Eng. & Comput. Sci., Peking Univ., Beijing, China]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University, School of Electrical Engineering and Computer Science, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"[Sch. of Electr. Eng. & Comput. Sci., Peking Univ., Beijing, China]","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058066577","display_name":"Tiejun Huang","orcid":"https://orcid.org/0000-0002-4234-6099"},"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":"Tiejun Huang","raw_affiliation_strings":["Peking University, School of Electrical Engineering and Computer Science, Beijing, China","[Sch. of Electr. Eng. & Comput. Sci., Peking Univ., Beijing, China]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University, School of Electrical Engineering and Computer Science, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"[Sch. of Electr. Eng. & Comput. Sci., Peking Univ., Beijing, China]","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.1677,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.96137286,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"23","issue":"11","first_page":"1849","last_page":"1864"},"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/T11019","display_name":"Image Enhancement Techniques","score":0.9962999820709229,"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":0.9954000115394592,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/background-subtraction","display_name":"Background subtraction","score":0.940582275390625},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8065669536590576},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.737647533416748},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6931324601173401},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6789731383323669},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.650299608707428},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6432235836982727},{"id":"https://openalex.org/keywords/foreground-detection","display_name":"Foreground detection","score":0.48040369153022766},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4154300391674042},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41391342878341675},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.36685019731521606}],"concepts":[{"id":"https://openalex.org/C32653426","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Background subtraction","level":3,"score":0.940582275390625},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8065669536590576},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.737647533416748},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6931324601173401},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6789731383323669},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.650299608707428},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6432235836982727},{"id":"https://openalex.org/C2779769447","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Foreground detection","level":4,"score":0.48040369153022766},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4154300391674042},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41391342878341675},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.36685019731521606},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tcsvt.2013.2248239","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2013.2248239","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Circuits and Systems for Video Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1499877760","https://openalex.org/W1573546770","https://openalex.org/W1603657930","https://openalex.org/W1891609420","https://openalex.org/W1969977005","https://openalex.org/W1987405870","https://openalex.org/W1990864775","https://openalex.org/W2048112589","https://openalex.org/W2049633694","https://openalex.org/W2050583479","https://openalex.org/W2062903088","https://openalex.org/W2092609388","https://openalex.org/W2096309046","https://openalex.org/W2102625004","https://openalex.org/W2104037217","https://openalex.org/W2115213191","https://openalex.org/W2123221155","https://openalex.org/W2125491588","https://openalex.org/W2128384066","https://openalex.org/W2128728535","https://openalex.org/W2134432876","https://openalex.org/W2141681031","https://openalex.org/W2143373691","https://openalex.org/W2157298759","https://openalex.org/W2158604775","https://openalex.org/W2159931533","https://openalex.org/W2164630676","https://openalex.org/W2171192355","https://openalex.org/W2188426398","https://openalex.org/W2430607491","https://openalex.org/W3142873477","https://openalex.org/W4234245929","https://openalex.org/W4255802862","https://openalex.org/W6629695367","https://openalex.org/W6683017119","https://openalex.org/W6687379313","https://openalex.org/W6718139592","https://openalex.org/W6837952794"],"related_works":["https://openalex.org/W2105103921","https://openalex.org/W2427283480","https://openalex.org/W2028059897","https://openalex.org/W2086414697","https://openalex.org/W1999137714","https://openalex.org/W2953123162","https://openalex.org/W2188430267","https://openalex.org/W4298195641","https://openalex.org/W3010714307","https://openalex.org/W1973030300"],"abstract_inverted_index":{"Background":[0],"subtraction":[1,20,55],"is":[2,88,134,194],"a":[3,28,47,83,124],"fundamental":[4],"preprocessing":[5],"step":[6],"in":[7,21,56],"many":[8],"surveillance":[9],"video":[10,74,230],"analysis":[11],"tasks.":[12],"In":[13],"spite":[14],"of":[15,31,61,68,118,216],"significant":[16],"efforts,":[17],"however,":[18],"background":[19,52,93,219],"crowded":[22,57,125],"scenes":[23],"remains":[24],"challenging,":[25],"especially,":[26],"when":[27,191],"large":[29],"number":[30],"foreground":[32],"objects":[33],"move":[34],"slowly":[35],"or":[36,80],"just":[37],"keep":[38],"still.":[39],"To":[40],"address":[41],"the":[42,72,107,116,119,168,173,180,188,192,199,205,217,224,228],"problem,":[43],"this":[44],"paper":[45],"proposes":[46],"selective":[48],"eigenbackground":[49,140,175,207],"method":[50,63,203,235],"for":[51,123,198,208],"modeling":[53],"and":[54,109,227],"scenes.":[58],"The":[59],"contributions":[60],"our":[62,202,234],"are":[64],"three-fold:":[65],"First,":[66],"instead":[67],"training":[69,108],"eigenbackgrounds":[70],"using":[71,149],"original":[73,97],"frames":[75,98,105],"that":[76,182,233],"may":[77],"contain":[78],"more":[79],"less":[81],"foregrounds,":[82],"virtual":[84,104],"frame":[85],"construction":[86],"algorithm":[87],"utilized":[89],"to":[90,101,136,142,165,171,178,211],"assemble":[91],"clean":[92],"pixels":[94,185],"from":[95],"different":[96],"so":[99],"as":[100,106],"construct":[102],"some":[103,150],"update":[110,152],"samples.":[111],"This":[112],"can":[113,186],"significantly":[114],"improve":[115],"purity":[117],"trained":[120,158],"eigenbackgrounds.":[121],"Second,":[122],"scene":[126],"with":[127,144],"diversified":[128],"environmental":[129],"conditions":[130],"(e.g.,":[131],"illuminations),":[132],"it":[133],"difficult":[135],"use":[137],"only":[138],"one":[139,170],"model":[141],"deal":[143],"all":[145,184],"these":[146],"variations,":[147],"even":[148],"online":[151,174],"strategies.":[153],"Thus":[154],"given":[155],"several":[156,237],"models":[157],"offline,":[159],"we":[160],"utilize":[161],"peak":[162],"signal-to-noise":[163],"ratio":[164],"adaptively":[166],"choose":[167],"optimal":[169,189],"initialize":[172],"model.":[176],"Third,":[177],"tackle":[179],"problem":[181],"not":[183],"obtain":[187,212],"results":[190],"reconstruction":[193],"performed":[195],"at":[196],"once":[197],"whole":[200],"frame,":[201],"selects":[204],"best":[206],"each":[209],"pixel":[210],"an":[213],"improved":[214],"quality":[215],"reconstructed":[218],"image.":[220],"Extensive":[221],"experiments":[222],"on":[223],"TRECVID-SED":[225],"dataset":[226,231],"Road":[229],"show":[232],"outperforms":[236],"state-of-the-art":[238],"methods":[239],"remarkably.":[240]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":8},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}