2D/3D automatic matching technique for 3D recovering of free form objects

This paper presents a new method for automatic matching between a free form 3D object and a single image. This matching can be used for object recognition and/or object 3D recovering. This kind of problem has raised a tremendous amount of interest in research fields such as computer vision, and more specifically in augmented reality. The original idea brought by our method is to use a photo-clinometric framework (such as shape from shading) in order to extract normal vectors information from the image. Our interest is focused on the distribution of angles between the surface normal vector and incident light vector. This information is discriminate for free form objects without symmetries, and one can show that it could be used to match between the image and model by using an aspect graph featuring this distribution.