Using Filtering Algorithm for Partial Similarity Search on 3D Shape Retrieval System

Abstract

Because 3D models are increasingly created and designed using computer graphics, computer vision, CAD medical imaging, and a variety of other applications, a large number of 3D models are being shared and offered on the Web. Large databases of 3D models, such as the Princeton Shape Benchmark Database [1], the 3D Cafe repository [2], and Aim@Shape network [3], are now publicly available. These datasets are made up of contributions from the CAD community, computer graphics artists, and the scientific visualization community. The problem of searching for a specific shape in a large database of 3D models is an important area of research. Text descriptors associated with 3D shapes can be used to drive the search process [4], as is the case for 2D images [5]. However, text descriptions may not be available, and furthermore may not apply for part-matching or similarity-based matching. Several content-based 3D shape retrieval algorithms have been proposed [6–8]. For the purpose of content-based 3D shape retrieval, various features of 3D shapes have been proposed [6–9]. However, these features are global features. In addition, it is difficult to effectively implement these features on relational databases because they include topological information. An efficient feature is proposed in Lu et al. [10] that can also be used in the partial similarity matching of shapes. However, they do not describe an efficient method to retrieve complex shapes by their partial similarity in Lu et al. [10] for a 3D shape database. In addition, the shock graph comparison-based retrieval method described in a previous paper [11] is based only on the topological information of the shape. A geometrical, partial similarity-based, and efficient method is needed to retrieve 3D shapes from a 3D shape database. In this chapter, we propose a novel filtering method to filter out shapes. The proposed method is based on geometrical information rather than on topological information alone. Shapes are removed from the candidate pool if the processing part of the key shape is not similar to any part of the potential candidate shape. We