{"id":"https://openalex.org/W1993531312","doi":"https://doi.org/10.1109/iccvw.2011.6130461","title":"Multi-scale multi-feature codebook-based background subtraction","display_name":"Multi-scale multi-feature codebook-based background subtraction","publication_year":2011,"publication_date":"2011-11-01","ids":{"openalex":"https://openalex.org/W1993531312","doi":"https://doi.org/10.1109/iccvw.2011.6130461","mag":"1993531312"},"language":"en","primary_location":{"id":"doi:10.1109/iccvw.2011.6130461","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvw.2011.6130461","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)","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/A5066415658","display_name":"Andrei Zaharescu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Andrei Zaharescu","raw_affiliation_strings":["Aimetis Corporation, Waterloo, ONT, Canada","Aimetis Corporation, 500 Weber Street North, Waterloo, Ontario, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aimetis Corporation, Waterloo, ONT, Canada","institution_ids":[]},{"raw_affiliation_string":"Aimetis Corporation, 500 Weber Street North, Waterloo, Ontario, Canada","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073249106","display_name":"Michael Jamieson","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Michael Jamieson","raw_affiliation_strings":["Aimetis Corporation, Waterloo, ONT, Canada","Aimetis Corporation, 500 Weber Street North, Waterloo, Ontario, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aimetis Corporation, Waterloo, ONT, Canada","institution_ids":[]},{"raw_affiliation_string":"Aimetis Corporation, 500 Weber Street North, Waterloo, Ontario, Canada","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1753","last_page":"1760"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9822999835014343,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9821000099182129,"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/codebook","display_name":"Codebook","score":0.9658125042915344},{"id":"https://openalex.org/keywords/background-subtraction","display_name":"Background subtraction","score":0.7649008631706238},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6805187463760376},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6791699528694153},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6596134901046753},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6185761094093323},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5270412564277649},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.48597586154937744},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24953636527061462},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.10125494003295898}],"concepts":[{"id":"https://openalex.org/C127759330","wikidata":"https://www.wikidata.org/wiki/Q637416","display_name":"Codebook","level":2,"score":0.9658125042915344},{"id":"https://openalex.org/C32653426","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Background subtraction","level":3,"score":0.7649008631706238},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6805187463760376},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6791699528694153},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6596134901046753},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6185761094093323},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5270412564277649},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.48597586154937744},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24953636527061462},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.10125494003295898},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccvw.2011.6130461","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvw.2011.6130461","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1499877760","https://openalex.org/W2013855924","https://openalex.org/W2033453961","https://openalex.org/W2040070350","https://openalex.org/W2096004068","https://openalex.org/W2096309046","https://openalex.org/W2096781172","https://openalex.org/W2098305432","https://openalex.org/W2102188949","https://openalex.org/W2111918405","https://openalex.org/W2115213191","https://openalex.org/W2115415549","https://openalex.org/W2122423951","https://openalex.org/W2125587358","https://openalex.org/W2130293653","https://openalex.org/W2135910427","https://openalex.org/W2140235142","https://openalex.org/W2148290050","https://openalex.org/W2149070968","https://openalex.org/W2158604775","https://openalex.org/W2161369719","https://openalex.org/W2164417971","https://openalex.org/W4234245929","https://openalex.org/W4248936881","https://openalex.org/W4251986860","https://openalex.org/W6629695367","https://openalex.org/W6660702617","https://openalex.org/W6674619037","https://openalex.org/W6679883415","https://openalex.org/W6681734982","https://openalex.org/W6683925110"],"related_works":["https://openalex.org/W2293149949","https://openalex.org/W2026099691","https://openalex.org/W4284672201","https://openalex.org/W2377486419","https://openalex.org/W2943202426","https://openalex.org/W2736714427","https://openalex.org/W2564343397","https://openalex.org/W2071787278","https://openalex.org/W2382329643","https://openalex.org/W2282723021"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,43,59,79,109],"novel":[4],"real-time":[5],"multi-feature":[6],"multi-scale":[7,81],"codebook-based":[8],"background":[9,29],"subtraction":[10],"algorithm,":[11],"targeted":[12],"for":[13],"challenging":[14,103],"surveillance":[15],"environments.":[16],"Our":[17],"contribution":[18],"is":[19,65,85,99,111],"three-fold.":[20],"First,":[21],"we":[22],"present":[23],"an":[24],"extension":[25],"of":[26],"the":[27,51,102],"Codebook":[28],"model":[30],"[4]":[31],"that":[32],"combines":[33],"multiple":[34],"features,":[35],"such":[36],"as":[37],"intensity,":[38],"colour":[39],"and":[40,54],"texture,":[41],"in":[42,87],"principled":[44],"way,":[45],"simultaneously":[46],"taking":[47],"into":[48],"account":[49],"both":[50],"feature's":[52],"confidence":[53,82],"its":[55],"similarity":[56],"score.":[57],"Second,":[58],"new":[60],"local":[61,74],"texture":[62],"pattern":[63,75],"descriptor":[64],"proposed,":[66],"entitled":[67],"Local":[68],"Ratio":[69],"Pattern,":[70],"generalizing":[71],"previously":[72],"successful":[73],"methods":[76],"[9].":[77],"Third,":[78],"generic":[80],"fusion":[83],"scheme":[84],"provided,":[86],"order":[88],"to":[89,119],"aggregate":[90],"individual":[91],"results":[92],"at":[93],"different":[94],"scales.":[95],"A":[96],"thorough":[97],"evaluation":[98],"performed":[100],"on":[101],"I2R":[104],"dataset":[105],"[8].":[106],"In":[107],"addition,":[108],"comparison":[110],"carried":[112],"out":[113],"with":[114],"other":[115],"competing":[116],"methods,":[117],"leading":[118],"state-of-the-art":[120],"performance.":[121]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":3},{"year":2014,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
