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

Abstract : The generic central camera model can describe any imaging system with a single effective viewpoint. We are interested in the self-calibration 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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Communication dans un congrès
The 8th Workshop on Omnidirectional Vision, Camera Networks and Non-classical Cameras - OMNIVIS, Oct 2008, Marseille, France. 2008
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  • HAL Id : inria-00325325, version 1

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Ferran Espuny, Jose I. Burgos Gil. Generic Self-calibration of Central Cameras from Two “Real” Rotational Flows. The 8th Workshop on Omnidirectional Vision, Camera Networks and Non-classical Cameras - OMNIVIS, Oct 2008, Marseille, France. 2008. 〈inria-00325325〉

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