While a large number of vision applications rely on the mapping between 3D scenes and their corresponding 2D camera images, the question that occurs to most researchers is what, in practice, are the most important determinants of camera calibration accuracy and what accuracy can be achieved within the practical limits of their environments. In response, we present a thorough study investigating the effects of training data quantity, measurement error, pixel coordinate noise, and the choice of camera model, on camera calibration results. Through this effort, we seek to determine whether expensive, elaborate setups are necessary, or indeed, beneficial, to camera calibration, and whether a high complexity camera model leads to improved accuracy. The results are first provided for a simulated camera system and then verified through carefully controlled experiments using real-world measurements.
Wei Sun, Jeremy R. Cooperstock