We propose a new semi-automatic calibration approach for projector-camera systems that - unlike existing auto-calibration approaches - additionally recovers the necessary global scale by projecting on an arbitrary object of known geometry from one view. Our method therefore combines surface registration with bundle adjustment optimization on points reconstructed from structured light projections. In simulations on virtual data and experiments with real data we demonstrate that our approach estimates the global scale robustly and is furthermore able to improve incorrectly guessed intrinsic and extrinsic calibration parameters.
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