Background estimation and adaptation model with light-change removal for heavily cown-sampled video surveillance signals

S.D. Cvetkovic, Peter Bakker, J. Schirris, P.H.N. With, de

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

12 Citations (Scopus)
88 Downloads (Pure)

Abstract

This paper describes a background-subtraction system with light change-detection which works on a luminance QCIF-size video signal for surveillance applications. The new proposed pixel background model is controlled by a statistical threshold and is robust for cluttered background and small object motions. Moreover, (or light-change detection, we introduce temporal prediction of pixel values to estimate trends while quickly adapting to scene changes to facilitate a very sensitive detection of moving targets. Experiments show that a local contrast enhancement applied prior to down-sampling improves detection sensitivity, arid combined with the shifted sealed difference and me Wronskian determinant operators provides the best background/foreground detection
Original languageEnglish
Title of host publicationProceedings of the IEEE International Conference on Image Processing (ICIP 2006), October 8-11, 2006, Atlanta, Georgia
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Pages1829-1832
ISBN (Print)1-4244-0480-0
DOIs
Publication statusPublished - 2009

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