Performance evaluation for full three-dimensional projector calibration methods in spatial augmented reality

Spatial Augment Reality (SAR) has presented itself to be an interesting tool for not only interesting ways to visualize information but to develop creative works in performance arts. The main challenge is to determine accurate geometry of a projection space and determine an efficient and effective way to project digital media and information to create an augmented space. In our previous implementation of SAR, we developed a projector-camera calibration approach using infrared markers. However, the projection suffers severe distortion due to the lack of depth information in the projection space. For this research, we propose to develop a RGBD sensor - projector system to replace our current projector-camera SAR system. Proper calibration between the camera or sensor and projector links vision to projection, answering the question of which point in camera space maps to what point in the space of projection. Calibration will resolve the problem of capturing the geometry of the space and allow us to accurately augment the surfaces of volumetric objects and features. In this work three calibration methods are examined for performance and accuracy. Two of these methods are existing adaptations of 2D camera - projector calibrations (calibration using arbitrary planes and ray-plane intersection) with our third proposed novel technique which utilizes point cloud information from the RGBD sensor directly. Through analysis and evaluation using re-projection error, results are presented, identifying the proposed method as practical and robust.