{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/49503"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/49503","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Online robust principal component analysis for background subtraction: a system evaluation on Toyota car data","abstract":"Robust Principal Component Analysis (RPCA) methods have become very popular in the past ten years. Many publications show that RPCA provides good results for background subtraction problems. In this thesis, we further the exploration to online versions of RPCA algorithms. The proposed Online Robust Principal Component Analysis (ORPCA) is used to process big data in a more efficient way. We also test the algorithm performances on the Toyota car data set provided by the Toyota Motor Corporation. Meanwhile, a comprehensive comparison of the algorithm performance is also shown based on testing results and running efficiency.","abstract_html":"Robust Principal Component Analysis (RPCA) methods have become very popular in the past ten years. Many publications show that RPCA provides good results for background subtraction problems. In this thesis, we further the exploration to online versions of RPCA algorithms. The proposed Online Robust Principal Component Analysis (ORPCA) is used to process big data in a more efficient way. We also test the algorithm performances on the Toyota car data set provided by the Toyota Motor Corporation. Meanwhile, a comprehensive comparison of the algorithm performance is also shown based on testing results and running efficiency.","abstract_has_math":false,"creators":["Xu, Xingqian"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Huang, Thomas S."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-05-30T16:47:30Z","date_published":"2014-05-30T16:47:30Z","updated_at":"2026-07-22T22:25:38Z","subjects":["Online RPCA","Robust Principal Component Analysis (RPCA)"],"languages":["en"],"rights":["Copyright 2014 Xingqian Xu"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/49503","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Huang, Thomas S."]},{"key":"dc:creator","label":"Author","values":["Xu, Xingqian"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2014-05-30T16:47:30Z","2014-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Online RPCA","Robust Principal Component Analysis (RPCA)"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2014 Xingqian Xu"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/49503"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Robust Principal Component Analysis (RPCA) methods have become very popular in the past ten years. 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