Charge Density-Based 3D Model Retrieval Using Bag-of-Feature

Abstract

As the number of 3D models is growing on the internet and other domain-specific datasets, the search and retrieval of such models are attracting a lot of attention. A shape descriptor it plays critical roles in the retrieval quality enhancement. In this paper we propose a new robust shape descriptor based on the distribution of charge density on the surface of a 3D model. After calculating the charge density for each triangular face of each model as local features, we utilize the Bag-of-Features framework to perform global matching using the local features. Our experiments on the McGill and PSB datasets show that the proposed descriptor is robust to a variety of modifications and transformations and offers a higher retrieving quality compared to other well-known approaches.