SIMILARITY MEASURE FOR SUPERQUADRICS

Superquadrics with parametric deformations are suitable models for use as solid primitives for describing a complicated 3-D object. Some dif ferent methods for the recovery of superquadric primitives from range data have been proposed, but there is still no effective similarity me asure for the matching task between two superquadrics in a 3-D object recognition system. The authors propose a similarity measure to evalua te the degree of shape similarity between two superquadric-based objec ts. This similarity measure is defined as the volume of regions bounde d by the surfaces of two 3-D objects. The proposed measure has been pr oved to be a metric. The metric value is computed by the Monte Carlo i ntegration method. The experimental results illustrate that the propos ed similarity measure is effective in matching a recovered superquadri c with a set of superquadrics in the model database.