Computer Graphics & Visual Computing (CGVC) 2016
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Browsing Computer Graphics & Visual Computing (CGVC) 2016 by Subject "Curve"
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Item Topological Visualisation Techniques for the Understanding of Lattice Quantum Chromodynamics (LQCD) Simulations(The Eurographics Association, 2016) Thomas, Dean P.; Borgo, Rita; Hands, Simon; Cagatay Turkay and Tao Ruan WanThe use of topology for visualisation applications has become increasingly popular due to its ability to summarise data at a high level. Criticalities in scalar field data are used by visualisation methods such as the Reeb graph and contour trees to present topological structure in simple graph based formats. These techniques can be used to segment the input field, recognising the boundaries between multiple objects, allowing whole contour meshes to be seeded as separate objects. In this paper we demonstrate the use of topology based techniques when applied to theoretical physics data generated from Quantum Chromodynamics simulations, which due to its structure complicates their use. We also discuss how the output of algorithms involved in topological visualisation can be used by physicists to further their understanding of Quantum Chromodynamics.Item Volumetric Spot Noise for Procedural 3D Shell Texture Synthesis(The Eurographics Association, 2016) Pavie, Nicolas; Gilet, Guillaume; Dischler, Jean-Michel; Galin, Eric; Ghazanfarpour, Djamchid; Cagatay Turkay and Tao Ruan WanIn this paper, we present an extension of the Locally Controlled Spot Noise and a visualization pipeline for volumetric fuzzy details synthesis. We extend the noise model to author volumetric fuzzy details using filtered 3D quadratic kernel functions convolved with a projective non-uniform 2D distribution of impulses. We propose a new method based on order independent splatting to compute a fast view dependent approximation of shell noise at interactive rates. Our method outperforms ray marching techniques and avoids aliasing artifacts, thus improving interactive content authoring feedback. Moreover, generated surface details share the same properties as procedural noise: they extend on potentially infinite surfaces, are defined in an extremely compact way, are non-repetitive, continuous (no discrete voxel-artifacts when zooming) and independent of the definition of the underlying surface (no surface parameterization is required).