Ghosting suppression for incremental principal component pursuit algorithms

Paul Rodríguez, Brendt Wohlberg

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

In video background modeling, ghosting occurs when an object that belongs to the background is assigned to the foreground. In the context of Principal Component Pursuit, this usually occurs when a moving object occludes a high contrast background object, a moving object suddenly stops, or a stationary object suddenly starts moving. Based on a previously developed incremental PCP method, we propose a novel algorithm that uses two simultaneous background estimates based on observations over the previous n1 and n2 (n1 C n2) frames in order to identify and diminish the ghosting effect. Our computational results show that the proposed method greatly improves both the subjective quality and accuracy as determined by the F-measure.

Original languageEnglish
Title of host publication2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages197-201
Number of pages5
ISBN (Electronic)9781509045457
DOIs
StatePublished - 19 Apr 2017
Event2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Washington, United States
Duration: 7 Dec 20169 Dec 2016

Publication series

Name2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings

Conference

Conference2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016
Country/TerritoryUnited States
CityWashington
Period7/12/169/12/16

Keywords

  • Ghosting
  • Incremental Principal Component Pursuit

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