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).

Date Published: 16 May 2013
PDF: 6 pages
Proc. SPIE 8740, Motion Imagery Technologies, Best Practices, and Workflows for Intelligence, Surveillance, and Reconnaissance (ISR), and Situational Awareness, 87400G (16 May 2013); doi: 10.1117/12.2015931

Published in SPIE Proceedings Vol. 8740:
Motion Imagery Technologies, Best Practices, and Workflows for Intelligence, Surveillance, and Reconnaissance (ISR), and Situational Awareness
Donnie Self, Editor(s)