Superquadric is a very flexible primitive in computer vision, it can represent a variety of 3D shapes by varying a few parameters. In this paper, a novel superquadric fitting based on radial Euclidean distance is proposed to evaluate the parameters of a superquadric. In the proposed superquadric fitting method, the initial parameters of a superquadric are first obtained by using the superellipse fitting method based on the geometric properties of the superquadric Once the initial parameters are obtained, the more accurate parameters are estimated by using iterative procedure involved optimization problem. The proposed superquadric fitting method is very usefu for object representation and recognition.
