Feature-Level and Descriptor-Level Information Fusion for Density-Based 3D Shape Descriptors

We address the 3D object retrieval problem using density-based shape descriptors. We explore first and second order local surface features and their multivariate combinations in the density estimation framework. We also experiment with descriptor level information fusion. The results, obtained using two different databases, Princeton Shape Benchmark and Sculpteur, show that, boosted with both feature level and descriptor level information fusion, the density-based shape description framework enables effective and efficient 3D object retrieval.