Similarity measure for superquadrics

Superquadrics with parametric deformations are suitable models for use as solid primitives for describing a complicated 3-D object. Some different methods for the recovery of superquadric primitives from range data have been proposed, but there is still no effective similarity measure for the matching task between two superquadrics in a 3-D object recognition system. The authors propose a similarity measure to evaluate the degree of shape similarity between two superquadric-based objects. This similarity measure is defined as the volume of regions bounded by the surfaces of two 3-D objects. The proposed measure has been proved to be a metric. The metric value is computed by the Monte Carlo integration method. The experimental results illustrate that the proposed similarity measure is effective in matching a recovered superquadric with a set of superquadrics in the model database.