The Kalman filter has been used successfully in different prediction applications or state determination of a system. One important field in computer vision is the object tracking. Different movement conditions and occlusions can hinder the vision tracking of an object. In this report we present the use of the Kalman filter in the vision tracking. We consider the capacity of the Kalman filter to allow small occlusions and also the use of the extended Kalman filter (EKF) to model complex movements of objects.
