No title
Accurately predicting head motion is essential for reducing motion-to-photon (MTP) latency in XR systems. However, standard evaluation practices often conflate true prediction error with residual calibration artifacts-such as global rotation bias, lever-arm offsets, or sub-frame time skews-even after alignment. These small but realistic miscalibrations can dominate reported errors and obscure the
