A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2011; you can also visit the original URL.
The file type is
Moving objects are usually detected by measuring the appearance change from a background model. The background model should adapt to slow changes such as illumination, but detect faster changes caused by moving objects. Particle filters do an excellent task in modeling non parametric distributions as needed for a background model, but may adapt too quickly to the foreground objects. A persistent particle filter is proposed, following bacterial persistence. Bacterial persistence is linked to thedoi:10.1109/icip.2010.5653118 dblp:conf/icip/Movshovitz-AttiasP10 fatcat:qbofjxymnfdq5jrnjqougc7egy