Generic Self-calibration of Central Cameras from Two “Real” Rotational Flows

The generic central camera model can describe any imaging system with a single effective viewpoint. We are interested in the selfcalibration of this model from only two rotations about non co-linear axes. Concisely, we show that the theoretical solution given in [1] performs correctly with real flow data, and that a simple iterative process can be used to improve the camera motion estimation. A method for the computation of smooth dense generic flows from rotational images is also presented and used in our experiments to compute “real” flows from both simulated and real images.

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