{"id":"https://openalex.org/W1999788504","doi":"https://doi.org/10.1109/tip.2012.2205700","title":"Object Tracking via Partial Least Squares Analysis","display_name":"Object Tracking via Partial Least Squares Analysis","publication_year":2012,"publication_date":"2012-06-22","ids":{"openalex":"https://openalex.org/W1999788504","doi":"https://doi.org/10.1109/tip.2012.2205700","mag":"1999788504","pmid":"https://pubmed.ncbi.nlm.nih.gov/22736691"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2012.2205700","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2012.2205700","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5115695336","display_name":"Qing Wang","orcid":"https://orcid.org/0000-0003-2138-996X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qing Wang","raw_affiliation_strings":["Department of Automation, National Laboratory for Information Science and Technology, Tsinghua University, Beijing 10084, China. qing-wang07@mails.tsinghua.edu.cn","Department of Automation, Tsinghua University, Beijing (China)"],"affiliations":[{"raw_affiliation_string":"Department of Automation, National Laboratory for Information Science and Technology, Tsinghua University, Beijing 10084, China. qing-wang07@mails.tsinghua.edu.cn","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing (China)","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100352725","display_name":"Feng Chen","orcid":"https://orcid.org/0000-0002-9054-6570"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Chen","raw_affiliation_strings":["Department of Automation, National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China","Department of Automation, Tsinghua University, Beijing (China)"],"affiliations":[{"raw_affiliation_string":"Department of Automation, National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing (China)","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100877238","display_name":"Wenli Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenli Xu","raw_affiliation_strings":["Department of Automation, National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China","Department of Automation, Tsinghua University, Beijing (China)"],"affiliations":[{"raw_affiliation_string":"Department of Automation, National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing (China)","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100980514","display_name":"Ming-Hsuan Yang","orcid":null},"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":["Department of Electrical Engineering and Computer Science, University of California, Merced, CA, USA","Dept. of Electr. Eng. & Comput. Sci., Univ. of California, Merced, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of California, Merced, CA, USA","institution_ids":["https://openalex.org/I156087764"]},{"raw_affiliation_string":"Dept. of Electr. Eng. & Comput. Sci., Univ. of California, Merced, CA, USA","institution_ids":["https://openalex.org/I156087764"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5115695336"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":13.6076,"has_fulltext":false,"cited_by_count":115,"citation_normalized_percentile":{"value":0.99141818,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"21","issue":"10","first_page":"4454","last_page":"4465"},"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/T11448","display_name":"Face recognition and analysis","score":0.9837999939918518,"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":0.9797999858856201,"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/discriminative-model","display_name":"Discriminative model","score":0.7953914403915405},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7895297408103943},{"id":"https://openalex.org/keywords/active-appearance-model","display_name":"Active appearance model","score":0.7378085851669312},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.708676278591156},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6821181774139404},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.6068147420883179},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.57230544090271},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5656211972236633},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.516091525554657},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5035104155540466},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.466537743806839},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.4600072205066681},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44117286801338196},{"id":"https://openalex.org/keywords/partial-least-squares-regression","display_name":"Partial least squares regression","score":0.4285150468349457},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.41760754585266113},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4165956974029541},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35118526220321655},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3111373782157898},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.12615451216697693}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7953914403915405},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7895297408103943},{"id":"https://openalex.org/C83248878","wikidata":"https://www.wikidata.org/wiki/Q344000","display_name":"Active appearance model","level":3,"score":0.7378085851669312},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.708676278591156},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6821181774139404},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6068147420883179},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.57230544090271},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5656211972236633},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.516091525554657},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5035104155540466},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.466537743806839},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.4600072205066681},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44117286801338196},{"id":"https://openalex.org/C22354355","wikidata":"https://www.wikidata.org/wiki/Q422009","display_name":"Partial least squares regression","level":2,"score":0.4285150468349457},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.41760754585266113},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4165956974029541},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35118526220321655},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3111373782157898},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.12615451216697693},{"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},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tip.2012.2205700","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2012.2205700","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmid:22736691","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/22736691","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.309.7701","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.309.7701","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://faculty.ucmerced.edu/mhyang/papers/tip12_pls_tracking.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7599999904632568,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1807914171","https://openalex.org/W2031489346","https://openalex.org/W2098854771","https://openalex.org/W2103876808","https://openalex.org/W2104271748","https://openalex.org/W2110920461","https://openalex.org/W2124490330","https://openalex.org/W2125078165","https://openalex.org/W2128027845","https://openalex.org/W2130320772","https://openalex.org/W2132103241","https://openalex.org/W2133199783","https://openalex.org/W2137225583","https://openalex.org/W2139047213","https://openalex.org/W2139269942","https://openalex.org/W2143715815","https://openalex.org/W2147533695","https://openalex.org/W2150000644","https://openalex.org/W2150057984","https://openalex.org/W2152668169","https://openalex.org/W2167089254","https://openalex.org/W2168682262","https://openalex.org/W2170865122","https://openalex.org/W2183648259","https://openalex.org/W2295262250","https://openalex.org/W2534262995","https://openalex.org/W2613779721","https://openalex.org/W2753461371","https://openalex.org/W4230884390","https://openalex.org/W4231340930","https://openalex.org/W6638399501","https://openalex.org/W6679366130","https://openalex.org/W6684274140"],"related_works":["https://openalex.org/W2609539975","https://openalex.org/W2786600129","https://openalex.org/W2132200263","https://openalex.org/W2102106825","https://openalex.org/W2982441782","https://openalex.org/W256589335","https://openalex.org/W2122378993","https://openalex.org/W2936520980","https://openalex.org/W2469120981","https://openalex.org/W2012200063"],"abstract_inverted_index":{"We":[0],"propose":[1],"an":[2],"object":[3,16,21,35,60],"tracking":[4,22,111,134],"algorithm":[5,86],"that":[6],"learns":[7],"a":[8,26,54],"set":[9],"of":[10,34,94,131],"appearance":[11,36,61,76,92],"models":[12,77],"for":[13,52,81],"adaptive":[14],"discriminative":[15,56],"representation.":[17],"In":[18],"this":[19],"paper,":[20],"is":[23,44,62],"posed":[24],"as":[25],"binary":[27],"classification":[28],"problem":[29,113],"in":[30,98],"which":[31],"the":[32,89,95,99,103,110,132],"correlation":[33],"and":[37,42,65,73,102,123],"class":[38],"labels":[39],"from":[40],"foreground":[41],"background":[43],"modeled":[45],"by":[46,115],"partial":[47],"least":[48],"squares":[49],"(PLS)":[50],"analysis,":[51],"generating":[53],"low-dimensional":[55],"feature":[57],"subspace.":[58],"As":[59],"temporally":[63],"correlated":[64],"likely":[66],"to":[67,125],"repeat":[68],"over":[69],"time,":[70],"we":[71],"learn":[72],"adapt":[74],"multiple":[75],"with":[78],"PLS":[79],"analysis":[80],"robust":[82],"tracking.":[83],"The":[84],"proposed":[85,133],"exploits":[87],"both":[88],"ground":[90],"truth":[91],"information":[93],"target":[96],"labeled":[97],"first":[100],"frame":[101],"image":[104],"observations":[105],"obtained":[106],"online,":[107],"thereby":[108],"alleviating":[109],"drift":[112],"caused":[114],"model":[116],"update.":[117],"Experiments":[118],"on":[119],"numerous":[120],"challenging":[121],"sequences":[122],"comparisons":[124],"state-of-the-art":[126],"methods":[127],"demonstrate":[128],"favorable":[129],"performance":[130],"algorithm.":[135]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":14},{"year":2017,"cited_by_count":17},{"year":2016,"cited_by_count":22},{"year":2015,"cited_by_count":23},{"year":2014,"cited_by_count":16},{"year":2013,"cited_by_count":10}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}