Wallflower: Principles and Practice of Background Maintenance

Background maintenance is a frequent element of video surveillance systems. We develop Wallflower, a threecomponent system for background maintenance: the pixellevel component performs Wiener filtering to make probabilistic predictions of the expected background; the region-level component fills in homogeneous regions of foreground objects; and the frame-level component detects sudden, global changes in the image and swaps in better approximations of the background. We compare our system with 8 other background subtraction algorithms. Wallflower is shown to outperform previous algorithms by handling a greater set of the difficult situations that can occur. Finally, we analyze the experimental results and propose normative principles for background maintenance.

• Type: Conference
• Year: 1999
• Where: ICCV
• Authors: Kentaro Toyama, John Krumm, Barry Brumitt, Brian Meyers
• Keywords: Background Maintenance, Background Subtraction Algorithms, Component Performs Wiener, Computer Vision, Frame-level Component, ICCV 1999, Region-level Component Fills