Robust self-calibration and Euclidean reconstruction via affine approximation
Fredrik Kahl, Anders Heyden · 2002
A new approach to self-calibration and Euclidean reconstruction from image sequences is presented. The key idea is to start with the affine camera model as a first approximation to obtain the affine 3D structure. It is then upgraded to an Euclidean structure and finally, refined by applying the full perspective camera model and bundle adjustment. The proposed scheme makes no assumption about the scene nor the camera motion. The only assumption required is that the camera has zero skew, which is a minimal condition in order to self-calibrate the camera. However, if other information is available about the camera, it can and should be incorporated. The method is robust and it also provides an estimate of the accuracy of the estimated parameters. Experiments are presented to illustrate the performance of the approach.