Color Correlogram Based Particle Filter for Object Tracking

Abstract

A novel color correlogram based particle filter was proposed for an object tracking in visual surveillance. By using the color correlogram as object feature, spatial information is incorporated into object representation, which yields a reliable likelihood description of the observation and prediction for tracking the objects accurately. The capability of the tracker to tolerate appearance changes like orientation changes, small scale changes, partial occlusions and background scene changes is demonstrated using real image sequences. Experimental evidence shows that the color correlogram is more effective than the traditional color histogram for objects tracking.