Visual Vocabulary Signature for 3D Object Retrieval and Partial Matching

Abstract

In this paper a novel object signature is proposed for 3D object retrieval and partial matching. A part-based representation is obtained by partitioning the objects into subparts and by characterizing each segment with different geometric descriptors. Therefore, a Bag ofWords framework is introduced by clustering properly such descriptors in order to define the so called 3D visual vocabulary. In this fashion, the object signature is defined as a histogram of 3D visual word occurrences. Several examples on the Aim@Shape watertight dataset demonstrate the versatility of the proposed method in matching either 3D objects with articulated shape changes or partially occluded or compound objects. In particular, a comparison with the methods that participated to the Shape Retrieval contest 2007 (SHREC) reports satisfactory results for both object retrieval and partial matching.