Non-manifold Multi-tessellation: From Meshes to Iconic Representations of Objects

Efficient Representations for Multi-resolution Modeling Efficient Representations for Multi-resolution Modeling Title: Efficient Representations for Multi-resolution Modeling

Thanks to improvement in simulation, high resolution scanning facilities and multidimensional medical imaging, the size of geometrical dataset is rapidly increasing, and huge datasets are commonly available. For this reason, Level-of-Detail (LOD) techniques have been proposed for triangle-based models of terrains and of the boundary of 3D manifold objects in a variety of applications. The basic...

Non-manifold Medial Surface Reconstruction from Volumetric Data

We present a method for medial surface reconstruction from volumetric data of thin-plate objects including junctions. Given medial voxels and distance fields computed from binarized volumes, we polygonize medial voxels by covering them with spherical supports and connecting the center points of the supports. These spherical supports are constructed by distributing spheres depending on the topol...

Non - Manifold Multi - Tessellation : from

Geometric Modeling of Multi-Material Printed Objects

We introduce a set of tools for interactive modeling of multi-material objects. We use non-manifold surface meshes to define complex objects, which can have multiple connected solid regions of different materials. Our suite of tools can create and edit non-manifold surfaces, while maintaining a consistent labeling of distinct regions. We also introduce a technique for generating approximate mat...

Constructing Smooth Non-Manifold Meshes of Multi-Labeled Volumetric Datasets

This paper presents a method for constructing consistent non-manifold meshes of multi-labeled volumetric datasets. This approach is different to traditional surface reconstruction algorithms which often only support extracting 2-manifold surfaces based on a binary voxel classification. However, in some – especially medical – applications, multi-labeled datasets, where up to eight differently la...