Computing high quality 3D models from multi-view stereo reconstruction is an active topic as can be seen in a recent review [15]. Most approaches make the strong assumption that the surface is Lambertian. In the case of a car, this hypothesis is not satisfied. Cars contain transparent parts and metallic surfaces that are highly reflective. To face these difficulties, we propose an approach to robustly reconstruct a 3D object in translation. Our contribution is a one-dimensional tracker that uses the vanishing point computed in a first pass. We applied it to video sequences of cars recorded from a static camera. Then, we introduce a local frame for the car and use it for creating a 3D rough model. The final result is sufficient for some applications where it is needed to estimate the size of the vehicle. This model can also be used as an initialization for more precise algorithms.
['Adrien Auclair', 'Laurent D. Cohen', 'Nicole Vincent']
A robust approach for 3D cars reconstruction