Abstract: To minimize the impact of motion-to-photo latency, we propose a Kalman filter algorithm with motion-to-photon latency jitter compensation to predict the user's head pose. First, we analyze and predict the motion-to-photon latency. Second, we select a head pose prediction method according to the correlation analysis results of the head motion. Further, we use the latency prediction result to compensate for the delay jitter in the head motion modeling and pose prediction. Compared to the original prediction method for the equipment, the average of the absolute error of attitude prediction decreases by 45.74%, 47.25%, and 40.96%. The maximum decreases by 11.49%, 26.34%, and 36.79. Moreover, the average of the absolute error of the position prediction decreases by 35.94%, 45.90%, and 55.81% and the maximum decreases by 1.05%, 25.60% and 44.74%.