Self-calibration of Central Cameras from Point Correspondences by Minimizing Angular Error
نویسندگان
چکیده
This paper proposes a generic self-calibration method for central cameras. The method requires two-view point correspondences and estimates both the internal and external camera parameters by minimizing angular error. In the minimization, we use a generic camera model which is suitable for central cameras with different kinds of radial distortion models. The proposed method can be hence applied to a large range of cameras from narrow-angle to fish-eye lenses and catadioptric cameras. Here the camera parameters are estimated by minimizing the angular error which does not depend on the 3D coordinates of the point correspondences. However, the error still has several local minima and in order to avoid these we propose a multi-step optimization approach. We demonstrate our method in experiments with synthetic and real data.
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تاریخ انتشار 2008