On visual object tracking using active appearance models

Abstract

Active appearance models provide an elegant framework for tracking objects. Using them in a deterministic algorithm to perforin tracking is not robust enough since no history is used of the object's movement and position. We discuss two approaches to rectify this situation. Both techniques are based on the particle filter. The first technique initialises the active appearance model search algorithm with a shape estimate obtained from an active contour tracker. A combination of a particle filter and an active appearance model forms the foundation for the second technique. Experimental results indicate the effectiveness of these techniques.