Robust Self-Calibration and Euclidean Reconstruction via Affine Approximation

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 affine 3D structure. It is then upgraded to Euclidean structure and finally, refined by applying the full perspective camera model. All steps in this procedure are described in detail and well-motivated. The method is robust and it also provides an estimate of the accuracy of the estimated parameters. The proposed method 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 and obtain a Euclidean reconstruction of the scene and the camera motion. However, if other information is available about the camera, for example constant intrinsic parameters, it can and should be incorporated to constrain the reconstruction. Experiments on both synthetic and real data are present..