Some systems can track head motion by constrained motion. The first step still involves feature finding and then the conversion of 2D feature position measurements into 3D estimates of position and orientation of the head used as a prediction. An extended Kalman filter formulation  can be used to provide an optimal linear estimate for dynamic systems. This filter is computationally efficient (recursive) and based on physical dynamics. The accuracy appears to be as good as a Polhemus magnetic sensor system.
Other models of prediction could be used such as a Hidden Markov model.