Generalized Image Acquisition and Analysis

Volume Stylizer: Tomography-based Volume Painting

Volumetric phenomena are an integral part of standard rendering, yet, no suitable tools to edit characteristic properties are available so far. Either simulation results are used directly, or modifications are high-level, e.g., noise functions to influence appearance. Intuitive artistic control is not possible. We propose a solution to stylize single-scattering volumetric effects. Emission, scattering and extinction become amenable to artistic control while preserving a smooth and coherent appearance when changing the viewpoint. Our approach lets the user define a number of target views to be matched when observing the volume from this perspective. Via an analysis of the volumetric rendering equation, we can show how to link this problem to tomographic reconstruction.

Projects

Intrinsic Shape Matching by Planned Landmark Sampling

Art Tevs, Alexander Berner, Michael Wand, Ivo Ihrke, Hans-Peter Seidel
In: Proceedings of EUROGRAPHICS 2011.



Abstract

Recently, the problem of intrinsic shape matching has received a lot of attention. A number of algorithms have been proposed, among which random-sampling-based techniques have been particularly successful due to their generality and efficiency. We introduce a new sampling-based shape matching algorithm that uses a planning step to find optimized "landmark" points. These points are matched first in order to maximize the information gained and thus minimize the sampling costs. Our approach makes three main contributions: First, the new technique leads to a significant improvement in performance, which we demonstrate on a number of benchmark scenarios. Second, our technique does not require any keypoint detection. This is often a significant limitation for models that do not show sufficient surface features. Third, we examine the actual numerical degrees of freedom of the matching problem for a given piece of geometry. In contrast to previous results, our estimates take into account unprecise geodesics and potentially numerically unfavorable geometry of general topology, giving a more realistic complexity estimate.
Project Page

Bibtex

@INPROCEEDINGS{Tevs11:plansac,
AUTHOR = {Art Tevs and Alexander Berner and Michael Wand and Ivo Ihrke and Hans-Peter Seidel},
EDITOR = {Deussen, Oliver and Chen, Min},
TITLE = {{Intrinsic Shape Matching by Planned Landmark Sampling}},
BOOKTITLE = {Computer Graphics Forum (Proc. EUROGRAPHICS)},
ORGANIZATION = {Eurographics},
PADDRESS = {Oxford, UK},
ADDRESS = {Llandudno, UK},
PUBLISHER = {Blackwell},
YEAR = {2011},
PAGES = {543--552},
}
Go to project list