Matching curved 3D object models to 2D images

Presents a method of locating known rigid 3D objects with arbitrary curved surfaces using a single image. A 3D object is modeled by a covering set of 2D silhouettes together with important internal edges. The model silhouette is derived by the curvature method of Basri and Ullman. Internal edges are computed using a stereo matching strategy. The pose of the observed object is determined by fitting the edgemap derived from the model images to the edgemap of the object. No salient matching primitives are used: correspondence is guided by the minimization of the over-all Euclidean distance between the model edgemap and the observed edgemap. Bench tests and simulations show that the matching technique converges for a broad range (entire aspect) of starting poses