Foreground estimation in motion imagery using multi-frame change detection techniques

Andrew J. Lingg; Brian D. Rigling

doi:10.1117/12.2015931

16 May 2013 Foreground estimation in motion imagery using multi-frame change detection techniques

Andrew J. Lingg, Brian D. Rigling

Proceedings Volume 8740, Motion Imagery Technologies, Best Practices, and Workflows for Intelligence, Surveillance, and Reconnaissance (ISR), and Situational Awareness; 87400G (2013) https://doi.org/10.1117/12.2015931
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

Abstract

Using multi-frame change detection methods, we estimate which pixels include objects that are in motion relative to the background. We utilize both a sequential statistical change detection method and a sparsity-based change detection method. We perform foreground estimation in videos in which the background is static as well as in images in which apparent background motion is induced by camera motion. We show the results of our techniques on the background subtraction data set from the Statistical Visual Computing Lab at the University of California, San Diego(UCSD).

Citation Download Citation

Andrew J. Lingg and Brian D. Rigling "Foreground estimation in motion imagery using multi-frame change detection techniques", Proc. SPIE 8740, Motion Imagery Technologies, Best Practices, and Workflows for Intelligence, Surveillance, and Reconnaissance (ISR), and Situational Awareness, 87400G (16 May 2013); https://doi.org/10.1117/12.2015931

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