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Camera calibration, crucial for computer vision tasks, often relies on planar calibration targets to calibrate the camera parameters. This work describes the design of a planar, fractal, self-identifying calibration pattern, which provides a high density of calibration points for a large range of magnification factors. An evaluation on ground truth data shows that the target provides very high accuracy over a wide range of conditions.

On the design of a fractal calibration pattern for improved camera calibration