A 3D shape retrieval method based on continuous spherical wavelet transform

Recently, many efforts have concentrated on finding efficient content based retrieval methods of 3D objects. In this paper, we proposed a new retrieval method. The method is constructed on a shape descriptor based on continuous spherical wavelet transform. Continuous 2D wavelet transform has extinct advantages in content, based image retrieval. The continuous wavelet transform can be extended from two dimensions to more dimensions, for example, spherical space, with the same properties. As a natural extension, continuous spherical wavelet transform can realize a spherical analysis. Therefore, we map a shape into a unit sphere by spherical parameterization, followed by continuous spherical wavelet transform of the spherical function. This method is our contribution. The result of the transform can be as a new descriptor and be used to match the dissimilarity of two shapes. We have examined our method on a small database of general objects and it is confirmed to be efficient.