{"id":"https://openalex.org/W1990659621","doi":"https://doi.org/10.1109/icassp.2013.6637955","title":"Robust visual tracking via a compact association of principal component analysis and canonical correlation analysis","display_name":"Robust visual tracking via a compact association of principal component analysis and canonical correlation analysis","publication_year":2013,"publication_date":"2013-05-01","ids":{"openalex":"https://openalex.org/W1990659621","doi":"https://doi.org/10.1109/icassp.2013.6637955","mag":"1990659621"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2013.6637955","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2013.6637955","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 Acoustics, Speech and Signal Processing","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/A5100631230","display_name":"Yuxia Wang","orcid":"https://orcid.org/0009-0003-1804-9021"},"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":"Yuxia Wang","raw_affiliation_strings":["Beijing Laboratory of Intelligent Infonnation Technology, School of Computer Science, Beijing Institute of Technology, Beijing, China","Beijing Lab. of Intell. Inf. Technol., Beijing Inst. of Technol., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Laboratory of Intelligent Infonnation Technology, School of Computer Science, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"Beijing Lab. of Intell. Inf. Technol., Beijing Inst. of Technol., Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083149989","display_name":"Qingjie Zhao","orcid":"https://orcid.org/0000-0002-3368-1290"},"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":"Qingjie Zhao","raw_affiliation_strings":["Beijing Laboratory of Intelligent Infonnation Technology, School of Computer Science, Beijing Institute of Technology, Beijing, China","Beijing Lab. of Intell. Inf. Technol., Beijing Inst. of Technol., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Laboratory of Intelligent Infonnation Technology, School of Computer Science, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]},{"raw_affiliation_string":"Beijing Lab. of Intell. Inf. Technol., Beijing Inst. of Technol., Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07967961,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"1764","last_page":"1768"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994000196456909,"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":0.9994000196456909,"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/T10838","display_name":"Animal Behavior and Welfare Studies","score":0.9537000060081482,"subfield":{"id":"https://openalex.org/subfields/3404","display_name":"Small Animals"},"field":{"id":"https://openalex.org/fields/34","display_name":"Veterinary"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9205999970436096,"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/canonical-correlation","display_name":"Canonical correlation","score":0.9231327772140503},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.9143266081809998},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.6849472522735596},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6503260731697083},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.6448676586151123},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6296108961105347},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.6055471301078796},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5904017090797424},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5048750042915344},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.47404763102531433},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.41913244128227234},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3406426012516022},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.21193653345108032}],"concepts":[{"id":"https://openalex.org/C153874254","wikidata":"https://www.wikidata.org/wiki/Q115542","display_name":"Canonical correlation","level":2,"score":0.9231327772140503},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.9143266081809998},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6849472522735596},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6503260731697083},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.6448676586151123},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6296108961105347},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.6055471301078796},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5904017090797424},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5048750042915344},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.47404763102531433},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.41913244128227234},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3406426012516022},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.21193653345108032},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"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/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/icassp.2013.6637955","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2013.6637955","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 Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1513768190","https://openalex.org/W1555148682","https://openalex.org/W1983772724","https://openalex.org/W1988712132","https://openalex.org/W2035379092","https://openalex.org/W2041175617","https://openalex.org/W2047589263","https://openalex.org/W2112419200","https://openalex.org/W2121193292","https://openalex.org/W2124490330","https://openalex.org/W2132103241","https://openalex.org/W2133140216","https://openalex.org/W2139047213","https://openalex.org/W2145948906","https://openalex.org/W2167089254","https://openalex.org/W2183648259","https://openalex.org/W2293873019","https://openalex.org/W2335728540","https://openalex.org/W2355165750","https://openalex.org/W2360451824","https://openalex.org/W2986028972","https://openalex.org/W4231340930","https://openalex.org/W6630587866","https://openalex.org/W6676866756","https://openalex.org/W6682039156","https://openalex.org/W6684274140","https://openalex.org/W6686234685","https://openalex.org/W6703065324","https://openalex.org/W7043678548"],"related_works":["https://openalex.org/W2579148721","https://openalex.org/W4387893611","https://openalex.org/W2347335694","https://openalex.org/W2091056927","https://openalex.org/W2067407580","https://openalex.org/W4317486777","https://openalex.org/W4389669152","https://openalex.org/W2038514069","https://openalex.org/W1967233468","https://openalex.org/W2132703645"],"abstract_inverted_index":{"We":[0,30],"propose":[1,79],"a":[2,109],"novel":[3],"correlation-based":[4],"incremental":[5],"tracking":[6,42],"algorithm":[7,83],"based":[8],"on":[9,98],"the":[10,35,56,64,68,89],"combination":[11],"of":[12,70,111],"principal":[13],"component":[14],"analysis":[15,20],"(PCA)":[16],"and":[17,62,91,94,118],"canonical":[18],"correlation":[19],"(CCA),":[21],"which":[22,87],"called":[23],"Principal":[24],"Component-Canonical":[25],"Correlation":[26],"Analysis":[27],"(P3CA)":[28],"tracker.":[29],"utilize":[31],"CCA":[32,71,92],"to":[33,54],"evaluate":[34],"target":[36],"goodness,":[37],"resulting":[38],"in":[39,48,67,114],"more":[40],"robust":[41],"than":[43,108],"using":[44],"holistic":[45],"information,":[46],"especially":[47],"handling":[49,115],"occlusion.":[50],"PCA":[51,90],"is":[52],"adopted":[53],"solve":[55],"Small":[57],"Sample":[58],"Size":[59],"(3S)":[60],"problem":[61],"reduce":[63],"computation":[65],"cost":[66],"generation":[69],"subspace.":[72],"To":[73],"account":[74],"for":[75,84],"appearance":[76,120],"variations,":[77],"we":[78],"an":[80],"online":[81],"updating":[82],"P3CA":[85],"tracker,":[86],"updates":[88],"cooperatively":[93],"synchronously.":[95],"Comparative":[96],"results":[97],"several":[99],"challenging":[100],"sequences":[101],"demonstrate":[102],"that":[103],"our":[104],"tracker":[105],"performs":[106],"better":[107],"number":[110],"state-of-the-art":[112],"methods":[113],"partial":[116],"occlusion":[117],"various":[119],"variations.":[121]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}