  Tracking objects in Computer Vision is a hard problem. Privacy and utility
concerns adds an extra layer of complexity over this problem. In this work we
consider the problem of maintaining privacy and utility while tracking an
object in a video stream using Kalman filtering. Our first proposed method
ensures that the localization accuracy of this object will not improve beyond a
certain level. Our second method ensures that the localization accuracy of the
same object will always remain under a certain threshold.
