3D model retrieval based on orthogonal projections

Recently with the development of 3D modeling and digitizing tools, more and more models have been created, which leads to the necessity of the technique of 3D model retrieval system. In this paper we investigate a new method for 3D model retrieval based on orthogonal projections. We assume that 3D models are composed of trigonal meshes. Algorithms proceed first by a normalization step in which the 3D models are transformed into canonical coordinates. Then each model is orthogonally projected onto six surfaces of the projected cube which contains it. A following step is feature extraction of the projected images which is done by moment invariants and polar radius Fourier transform. The feature vector of each 3D model is composed of the features extracted from projected images with different weights. Our system validates that this means can distinguish 3D models effectively. Experiments show that our method performs quit well.