3D Model Retrieval with Spherical Harmonics and Moments

We consider 3D object retrieval in which a polygonal mesh serves as a queryand similar objects are retrieved from a collection of 3D objects. Algorithms proceed first bya normalization step in which models are transformed into canonical coordinates. Second, feature vectors are extracted and compared with those derived from normalized models in the search space. In the feature vector space nearest neighbors are computed and ranked. Retrieved objects are displayed for inspection, selection, and processing. Our feature vectors are based on rays cast from the center of mass of the object. For each raythe object extent in the raydirection yields a sample of a function on the sphere. We compared two kinds of representations of this function, namelyspherical harmonics and moments. Our empirical comparison using precision-recall diagrams for retrieval results in a data base of 3D models showed that the method using spherical harmonics performed better.