Abstract: Shape reconstruction from raw point sets is a hot research topic. Point sets are increasingly available as primary input source, since low-cost acquisition methods are largely accessible nowadays, and these sets are more noisy than used to be. Standard reconstruction methods rely on normals or signed distance functions, and thus many methods aim at estimating these features. Human vision can however easily discern between the inside and the outside of a dense cloud even without the support of fancy measures. We propose, here, a perceptual method for estimating an indicator function for the shape, inspired from image-based methods. The resulting function nicely approximates the shape, is robust to noise, and can be used for direct isosurface extraction or as an input for other accurate reconstruction methods.
Authors: F. Guggeri, R. Scateni, R. Pajarola.
Shape Reconstruction from Raw Point Clouds using Depth Carving.
EuroGraphics Conference 2012 (short presentations), 33-36.
Cagliari, Italia, Maggio 2012.
Abstract: In this paper we present the work in progress along with some preliminary research results in the field of Computational Geometry and Mesh Processing obtained by the Computer Graphics Group of the University of Cagliari, Italy. We focus on the work in mesh analysis by introducing the development of a lightweight visualization and processing tool that helped expanding the aims of the group by letting the students from the University move their first steps in Computer Graphics. We show some results obtained by the group with the focus on the usefulness of a common framework of reference.
Abstract: In this paper we propose an optimization of the Shape Diameter Function (SDF) that we call Accelerated SDF (ASDF). We discuss in detail the advantages and disadvantages of the original SDF definition, proposing theoretical and practical approaches for speedup and approximation. Using Poisson-based interpolation we compute the SDF value for a small subset of randomly distributed faces and propagate the values over the mesh. We show the results obtained with ASDF versus SDF in terms of timings and error.
Abstract: Recent advances in acquisition and modelling techniques led to generating an exponentially increasing amount of 3D shapes available both over the Internet or in specific databases. While the number grows it becomes more and more difficult to keep an organized knowledge over the content of this repositories. It is commonly intended that in the near future 3D shapes and models will be indexed and searched using procedure and instruments mimicking the same operations performed on images while using algorithms, data structures and instruments peculiar to the domain. In this context it is thus important to have tools for automatic characterization of 3D shapes, and skeletons and partitions are the two most prominent ones among them. In this paper we will describe an experience of building some of this tools on the top of a popular and robust library for manipulating meshes (OpenMesh). The preliminary results we present are promising enough to let us expect that the sum of the tools will be a useful aid to improving indexing and retrieval of digital 3D objects. The work presented here is part of a larger project: Three-Dimensional Shape Indexing and Retrieval Techniques (3-SHIRT), in collaboration with the Universities of Genoa, Padua, Udine, and Verona.