Abstract : We present a novel approach to reconstruct a 3D object from images corresponding to two different viewpoints: we estimate the skeleton of the object instead of its surface. The originality of the method is to be able to reconstruct a tubular object with a limited number of input images. Unlike classical reconstruction methods, like multi-view stereo or more recently structure-from-motion, this approach does not rely on interest points but estimates the topology of the object and derives its surface. Our contribution are twofold. First, given two perspective images of the 3D shape, the projection of the skeleton is computed in 2D. Secondly the 3D skeleton is reconstructed from the two projections using triangulation and matching. A mesh is finally derived for each skeleton branch.