Geometry image matching for similarity estimation of 3D shapes

We describe our preliminary findings in applying the spherical parametrization and geometry images to the task of 3D shape matching and similarity based comparison of polygon soup models. Unlike traditional approach where multiple 2D views of the same object are required to capture the relevant geometry features, our proposed technique uses spherical parametrization and geometry images for 3D shape matching. This technique reduces the problem to the 2D space without computing 2D projections and guarantees the preservation of small details. Moreover, we take advantage from the hierarchical nature of the parametrization process, through the progressive mesh simplification, to derive a multiresolution analysis technique. Our proposed algorithm is invariant to similarity transformations such as rotation and scaling. The efficiency of this approach is discussed through a set of experiments