{"id":"https://openalex.org/W2167089254","doi":"https://doi.org/10.1109/cvpr.2009.5206737","title":"Visual tracking with online Multiple Instance Learning","display_name":"Visual tracking with online Multiple Instance Learning","publication_year":2009,"publication_date":"2009-06-01","ids":{"openalex":"https://openalex.org/W2167089254","doi":"https://doi.org/10.1109/cvpr.2009.5206737","mag":"2167089254"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2009.5206737","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2009.5206737","pdf_url":null,"source":{"id":"https://openalex.org/S4363607795","display_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","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/A5051339229","display_name":"Boris Babenko","orcid":"https://orcid.org/0000-0002-3013-3678"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Boris Babenko","raw_affiliation_strings":["University of California, San Diego, USA"],"affiliations":[{"raw_affiliation_string":"University of California, San Diego, USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100418319","display_name":"Ming\u2013Hsuan Yang","orcid":"https://orcid.org/0000-0003-4848-2304"},"institutions":[{"id":"https://openalex.org/I156087764","display_name":"University of California, Merced","ror":"https://ror.org/00d9ah105","country_code":"US","type":"education","lineage":["https://openalex.org/I156087764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ming-Hsuan Yang","raw_affiliation_strings":["University of California, Merced, USA"],"affiliations":[{"raw_affiliation_string":"University of California, Merced, USA","institution_ids":["https://openalex.org/I156087764"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018609918","display_name":"Serge Belongie","orcid":"https://orcid.org/0000-0002-0388-5217"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California, San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Serge Belongie","raw_affiliation_strings":["University of California, San Diego, USA"],"affiliations":[{"raw_affiliation_string":"University of California, San Diego, USA","institution_ids":["https://openalex.org/I36258959"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5051339229"],"corresponding_institution_ids":["https://openalex.org/I36258959"],"apc_list":null,"apc_paid":null,"fwci":38.0707,"has_fulltext":false,"cited_by_count":1806,"citation_normalized_percentile":{"value":0.99820467,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"983","last_page":"990"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9970999956130981,"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/T10057","display_name":"Face and Expression Recognition","score":0.989799976348877,"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":0.7554984092712402},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6139316558837891},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5740044116973877},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.5444052219390869},{"id":"https://openalex.org/keywords/online-learning","display_name":"Online learning","score":0.4852123558521271},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.481818825006485},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3671143054962158},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.2237856388092041},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.08841106295585632}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7554984092712402},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6139316558837891},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5740044116973877},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.5444052219390869},{"id":"https://openalex.org/C2986087404","wikidata":"https://www.wikidata.org/wiki/Q15946010","display_name":"Online learning","level":2,"score":0.4852123558521271},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.481818825006485},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3671143054962158},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.2237856388092041},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.08841106295585632},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cvpr.2009.5206737","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2009.5206737","pdf_url":null,"source":{"id":"https://openalex.org/S4363607795","display_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.192.9575","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.192.9575","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://staff.science.uva.nl/%7Ecgmsnoek/pub/readinggroup/TrackingMIL_CVPR2009.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.210.4510","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.210.4510","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://vision.ucsd.edu/sites/default/files/miltrack_cvpr09_9.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7799999713897705}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1678356000","https://openalex.org/W1807914171","https://openalex.org/W1988790447","https://openalex.org/W2000326692","https://openalex.org/W2024046085","https://openalex.org/W2108745803","https://openalex.org/W2110119381","https://openalex.org/W2117082318","https://openalex.org/W2118340964","https://openalex.org/W2120458963","https://openalex.org/W2121193292","https://openalex.org/W2128027845","https://openalex.org/W2139047213","https://openalex.org/W2146159678","https://openalex.org/W2150000644","https://openalex.org/W2152066136","https://openalex.org/W2155714768","https://openalex.org/W2159128898","https://openalex.org/W2162919312","https://openalex.org/W2164598857","https://openalex.org/W2166010828","https://openalex.org/W2168682262","https://openalex.org/W2295262250","https://openalex.org/W2613779721","https://openalex.org/W6638399501","https://openalex.org/W6676245398","https://openalex.org/W6677799911","https://openalex.org/W6679366130"],"related_works":["https://openalex.org/W2084086966","https://openalex.org/W2023861399","https://openalex.org/W2730915376","https://openalex.org/W2626306547","https://openalex.org/W2021396365","https://openalex.org/W2394134009","https://openalex.org/W2119515433","https://openalex.org/W2807619505","https://openalex.org/W2009561238","https://openalex.org/W2158788032"],"abstract_inverted_index":{"In":[0,16,96],"this":[1,97],"paper,":[2],"we":[3,99],"address":[4],"the":[5,49,52,60,71,77,89],"problem":[6],"of":[7,20,108],"learning":[8,111],"an":[9,44],"adaptive":[10],"appearance":[11],"model":[12],"for":[13,135],"object":[14,50,136],"tracking.":[15],"particular,":[17],"a":[18,40,120,130],"class":[19],"tracking":[21,137],"techniques":[22],"called":[23],"\u201ctracking":[24],"by":[25,58],"detection\u201d":[26],"have":[27],"been":[28],"shown":[29],"to":[30,47,64,82,119],"give":[31],"promising":[32],"results":[33,141],"at":[34],"real-time":[35,143],"speeds.":[36],"These":[37],"methods":[38],"train":[39],"discriminative":[41],"classifier":[42,55,90],"in":[43,76],"online":[45,132],"manner":[46],"separate":[48],"from":[51,70],"background.":[53],"This":[54],"bootstraps":[56],"itself":[57],"using":[59,102],"current":[61,72],"tracker":[62,78,123],"state":[63],"extract":[65],"positive":[66],"and":[67,91,115],"negative":[68],"examples":[69],"frame.":[73],"Slight":[74],"inaccuracies":[75],"can":[79,92,116],"therefore":[80,117],"lead":[81,118],"incorrectly":[83],"labeled":[84],"training":[85],"examples,":[86],"which":[87],"degrades":[88],"cause":[93],"further":[94],"drift.":[95],"paper":[98],"show":[100],"that":[101,138],"Multiple":[103],"Instance":[104],"Learning":[105],"(MIL)":[106],"instead":[107],"traditional":[109],"supervised":[110],"avoids":[112],"these":[113],"problems,":[114],"more":[121],"robust":[122],"with":[124,142],"fewer":[125],"parameter":[126],"tweaks.":[127],"We":[128],"present":[129],"novel":[131],"MIL":[133],"algorithm":[134],"achieves":[139],"superior":[140],"performance.":[144]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":35},{"year":2022,"cited_by_count":38},{"year":2021,"cited_by_count":63},{"year":2020,"cited_by_count":87},{"year":2019,"cited_by_count":134},{"year":2018,"cited_by_count":151},{"year":2017,"cited_by_count":194},{"year":2016,"cited_by_count":204},{"year":2015,"cited_by_count":196},{"year":2014,"cited_by_count":205},{"year":2013,"cited_by_count":160},{"year":2012,"cited_by_count":132}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
