Transform-based methods for indexing and retrieval of 3D objects

Abstract

We compare two transform-based indexing methods for retrieval of 3D objects. We apply 3D discrete Fourier transform (DFT) and 3D radial cosine transform (RCT) to the voxelized data of 3D objects. Rotation invariant features are derived from the coefficients of these transforms. Furthermore we compare two different voxel representations, namely, binary denoting object and background space, and continuous after distance transformation. In the binary voxel representation the voxel values are simply set to 1 on the surface of the object and 0 elsewhere. In the continuous-valued representation the space is filled with a function of distance transform. The rotation invariance properties of the DFT and RCT schemes are analyzed. We have conducted retrieval experiments on the Princeton Shape Benchmark and investigated the retrieval performance of the methods using several quality measures.