Common self-polar triangle of separate circles for light field camera calibration

Due to the trade-off between spatial resolution and angular resolution of the light field, it is difficult to extract high precision corner points and line features from light fields for calibration. A novel calibration pattern of separate circles is designed, and a light field camera calibration method based on common self-polar triangle with respect to separate circles is proposed in this paper. First, we explore the uniquity and reconstruction of common self-polar triangle with respect to sperate circles. Then, based on projections of the multi-projection-center model on the plane and conic, the common self-polar triangle on the sub-aperture image is reconstructed and used to estimate planar homography. Finally, a light field camera calibration algorithm is then proposed, including linear initialization and non-linear optimization. Experimental results on both synthetic and real data have verified the effectiveness and robustness of the method and algorithm proposed.

Off-Line Camera-Based Calibration for Optical See-Through Head-Mounted Displays

In recent years, the entry into the market of self contained optical see-through headsets with integrated multi-sensor capabilities has led the way to innovative and technology driven augmented reality applications and has encouraged the adoption of these devices also across highly challenging medical and industrial settings. Despite this, the display calibration process of consumer level systems is still sub-optimal, particularly for those applications that require high accuracy in the spatial alignment between computer generated elements and a real-world scene. State-of-the-art manual and automated calibration procedures designed to estimate all the projection parameters are too complex for real application cases outside laboratory environments. This paper describes an off-line fast calibration procedure that only requires a camera to observe a planar pattern displayed on the see-through display. The camera that replaces the user’s eye must be placed within the eye-motion-box of the see-through display. The method exploits standard camera calibration and computer vision techniques to estimate the projection parameters of the display model for a generic position of the camera. At execution time, the projection parameters can then be refined through a planar homography that encapsulates the shift and scaling effect associated with the estimated relative translation from the old camera position to the current user’s eye position. Compared to classical SPAAM techniques that still rely on the human element and to other camera based calibration procedures, the proposed technique is flexible and easy to replicate in both laboratory environments and real-world settings.