Abstract. Three-dimensional shape matching is a young research field concerning the content-based comparison of 3D models. Several applications have been proposed so far, remarking its potential as support in computer graphics and high-level computer vision tasks. Similarly, a lot of research has been done to tackle the shape matching problem. As a result, there is a large amount of approaches and techniques in the literature. This tutorial gives an overview of three-dimensional shape matching and its applications in retrieval and recognition. In addition, we emphasize the importance of shape matching in computer graphics and computer vision as witnessed in recent researches. Our goal is to cover the relevant aspects of the field, presenting part of the state of the art and showing the existing and potential applications. Also, demos will be used to illustrate concepts and techniques. This will allow participants to easily understand the background of shape matching.
In order to run the demos provided here, some software requirements need to be properly installed: the toolbox graph (for reading and plotting meshes), the Toolbox Fast Marching (to compute geodesic distances in meshes, or you can use any other package for this purpose), the MeshLP package (to compute the Laplace-Beltrami operator) and MATLAB. In addition, the meshes used in the tutorial belong to the TOSCA dataset. You should download the dataset and extract the meshes in the same folder as demos.
We also provide our own tools (e.g. Harris 3D, the adaptive clustering, etc.) as MEX files. These tools are only available for 64-bits Linux platforms. If you need support for a different platform, please do not hesitate in contact us for providing the source code.
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