Practical Pan-Tilt-Zoom-Focus Camera Calibration for Augmented Reality

Abstract

While high-definition cameras with automated zoom lenses are widely used in broadcasting and film productions, there have been no practical calibration methods working without special hardware devices. We propose a practical method to calibrate pan-tilt-zoom-focus cameras, which takes advantages from both pattern-based and rotation-based calibration approaches. It uses patterns whose positions are only roughly known a priori, with several image samples taken at different rotations. The proposed method can find the camera view’s translation along the optical axis caused by zoom and focus operations, which has been neglected in most rotation-based algorithms. We also propose a practical focus calibration technique that is applicable even when the image is too defocused for the patterns to be detected. The proposed method is composed of two separate procedures – zoom calibration and focus calibration. Once the calibration is done for all zoom settings with a fixed focus setting, the remaining focus calibration is fully automatic. We show the accuracy of the proposed method by comparing it to the algorithm most widely used in computer vision. The proposed algorithm works also well for real cameras with translation offsets.