  The immersion and the interaction are the important features of the driving
simulator. To improve these characteristics, this paper proposes a low-cost and
mark-less driver head tracking framework based on the head pose estimation
model, which makes the view of the simulator can automatically align with the
driver's head pose. The proposed method only uses the RGB camera without the
other hardware or marker. To handle the error of the head pose estimation
model, this paper proposes an adaptive Kalman Filter. By analyzing the error
distribution of the estimation model and user experience, the proposed Kalman
Filter includes the adaptive observation noise coefficient and loop closure
module, which can adaptive moderate the smoothness of the curve and keep the
curve stable near the initial position. The experiments show that the proposed
method is feasible, and it can be used with different head pose estimation
models.
