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.