A stereo display of a computer model adds relative depth information through binocular disparity. When the stereo viewing transformations are generated using knowledge of the viewer's head position, absolute depth positioning can be determined and a much more tangible presentation is created. The amount of benefit derived from such a display is dependent on the stability of the model's image as the head moves. To create this apparent stability the computer must display a different stereo view for each different position of the head, and update as often as possible. the image's stability is a direct result of both update rate and the ability to accurately determine the position of the head at the moment the stereo pair is presented. We present here the stereo transformations that we use and the results of our experiments in the area of accurately tracking the position of the head. We have tried various techniques to reduce noise in the stream of head position and orientation data. We have also tried prediction techniques on the same stream of data. We also describe applications of the technique, evaluating its utility with respect to different data types, data representations, and tasks.