Euclidian Shape and Motion from Multiple Perspective Views by Affine Iterations
Résumé
In this paper we describe a method for solving the Euclidean reconstruction problem with a perspective camera model by incrementally performing an Euclidean reconstruction with either a weak or a para perspective camera model. With respect to other methods that compute shape and motion from a sequence of images with a calibrated perspective camera, this method converges in a few iterations, is computationnaly efficient, and does not suffer from the non linear nature of the problem. With respect to factorization and/or affine-invariant methods, this method solves for the sign (reversal) ambiguity in a very simple way and provides much more accurate reconstructions results. We give a detailed account of the method, analyse its convergence based on numerical and experimental considerations, and test its efficiency both with synthetic and real data.