SHREC’08 entry: Local volumetric features for 3D model retrieval

In this paper, we describe a method of shape-based 3D model retrieval that employs a set of 3D, local, multi-scale features extracted from a voxel representation of a 3D model to be compared. The method first convert a surface based 3D model into a voxel model. Then, a novel 3D extension of the popular 2D image feature, the Scale Invariant Feature Transform by David Lowe, is applied to extract a set of 3D local features. The 3D feature is invariant to rotation, uniform scaling, and translation in 3D space. A 3D model typically yields thousands of such local 3D features. Our method extracts thousands of 3D local features from a model to compare its shape. Our evaluation showed that the method is quite effective, achieving Means First Tier of 58% for the Query Set 1 of the SHREC’08 Generic Models Track.