MoiréPose: ultra high precision camera-to-screen pose estimation based on Moiré pattern

Camera tracking has become a key technology for various application scenarios, especially for AR-based camera-to-screen interaction. Demand for subtle motion detection in camera tracking makes it essential to explore the six degrees of freedom (6-DoF) pose detection with ultra-high precision. In this paper, we propose a novel sensing method MoiréPose to achieve ultra-high precision on the camera's 6-DoF pose estimation. The purpose of MoiréPose is to derive the camera's 3-DoF position and 3-DoF posture relative to the screen according to the captured moiré pattern, which is produced by the superposition of the camera's Color Filter Array (CFA) and the screen raster projected onto the CFA layer. Based on moiré pattern's high sensitivity to 6-DoF pose movement and robustness to the environmental interference in the frequency domain, we propose a spectrogram-based method to realize the camera's 6-DoF detection with ultra-high precision. Moreover, we propose a thumbnail-based method to effectively extend the working range of MoiréPose, so as to realize pervasive camera-to-screen interaction. We have implemented a prototype system and evaluate the performance in real-world environments. Extensive experiment results show that MoiréPose achieves an average position error of 7.5mm and an overall posture error of 1.66°.