AbstractInterest in three-dimensional shape retrieval is currently increasing, driven by two important reasons — the rapid increase of the amount of multimedia data and a noticeable advance in computer hardware and software during recent years. Presently, it is possible to retrieve complicated 3D models in a reasonable span of time thanks to the use of sophisticated 3D shape description algorithms, a feat which was unthinkable a few years ago. The main issue is the efficiency of the approaches, which must work both quickly and reliably. Hence, in this paper four 3D shape description algorithms — Extended Gaussian Image, Shape Distributions, Shape Histograms and Light Field Descriptor — were experimentally compared in order to determine which was most effective. As it turned out, the latter obtained the best retrieval result.
A Three-Dimensional Shape Description Algorithm Based on Polar-Fourier Transform for 3D Model Retrieval