A recursive fitting-and-splitting algorithm for 3-D object modeling using superquadrics

The paper proposes a new approach to 3D object modeling by integrating superquadric-fitting and segmentation into a top-down, recursive algorithm. Given sensor data, which are a set of multiview range data covering the whole object surface, the method begins with an initial approximation of the object by fitting a single superquadric. The fitting residuals are then examined to pick up data points either in deep concave regions or too far away from the approximating surface. A dividing plane is extracted from the points to partition the original data set into two disjoint subsets, which are further treated respectively with the same fitting-and-splitting scheme. This process is repeated until the whole data are decomposed into primitive superquadrics all within some preset error tolerance