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 complete tubular 3D object from only two input images. Unlike classical reconstruction methods like multiview stereo, this approach does not rely on interest points but estimates the topology of the object and derives its surface. Our contributions are twofold. First, given two perspective images of the 3D shape, the projection of the skeleton is computed in 2D. Second the 3D skeleton is reconstructed from the two projections using triangulation and matching. A mesh is finally derived for each skeleton branch.