Predictive windows for delay compensation in telepresence applications

Predictive Kalman filters can be used to predict positions of a mouse when it is operated under some basic assumptions. This prediction can be used to estimate what portions of a larger image an operator wants to view. This paper discusses theory and experimentation being done at the University of Alberta using predictive Kalman filters to provide predictive windows for low bandwidth telepresence applications. We compare several state models used in prediction with each other and also with having no prediction, both with numerical measures, and on human subjects. We show that the constant velocity model provides the best prediction results