Welcome to the Computer Graphics Group at RWTH Aachen University!

The research and teaching activities at our institute focus on geometry acquisition and processing, on interactive visualization, and on related areas such as computer vision, photo-realistic image synthesis, and ultra high speed multimedia data transmission.

In our projects we are cooperating with various industry companies as well as with academic research groups around the world. Results are published and presented at high-profile conferences and symposia. Additional funding sources, among others, are the Deutsche Forschungsgemeinschaft and the European Union.


Leif Kobbelt gave an invited talk at the Symposium on Geometry and Computational Design in Vienna.

Nov. 30, 2015

Leif Kobbelt gave an invited keynote presentation at the 24th International Meshing Roundtable in Austin, TX.

Oct. 15, 2015

Visual Computing Institute organizes this year's VMV & GCPR

The Visual Computing Institute organizes this year's VMV & GCPR conferences which will take place in parallel on October 07-09, 2015. For more information, please visit the official joint website.

Oct. 7, 2015

Prof. Dr. Leif Kobbelt has been appointed to Academia Europaea

Prof. Dr. Leif Kobbelt from the Visual Computing Institute at RWTH Aachen has been appointed to Academia Europaea. The Academia Europaea is one of the most prestigious European academies for scientists from all disciplines, who are leaders in their respective fields (top 1%). Objective of the Academia Europaea is to inform the public about current scientific topics and trends and to provide European research institutions and governments with independent advice on scientific issues.

For further information, please visit:

Oct. 6, 2015

We have a paper on Quantized Global Parametrization at SIGGRAPH Asia 2015.

Oct. 3, 2015


Researchers with a substantial track record are invited to submit their application by May 31st 2015. More details can be found in the official announcement. If you have further questions, please contact Prof. Dr. Leif Kobbelt directly.

May 31, 2015

Recent Publications

Reduced-Order Shape Optimization Using Offset Surfaces

ACM Transactions on Graphics (TOG), 34(4), 2015
Proceedings of the 2015 SIGGRAPH Conference

Given the 2-manifold surface of a 3d object, we propose a novel method for the computation of an offset surface with varying thickness such that the solid volume between the surface an its offset satisfies a set of prescribed constraints and at the same time minimizes a given objective functional. Since the constraints as well as the objective functional can easily be adjusted to specific application requirements, our method provides a flexible and powerful tool for shape optimization. We use manifold harmonics to derive a reduced-order formulation of the optimization problem which guarantees a smooth offset surface and speeds up the computation independently from the input mesh resolution without affecting the quality of the result. The constrained optimization problem can be solved in a numerically robust manner with commodity solvers. Furthermore, the method allows to simultaneously optimize an inner and an outer offset in order to increase the degrees of freedom. We demonstrate our method in a number of examples where we control the physical mass properties of rigid objects for the purpose of 3d printing.


Quantized Global Parametrization

SIGGRAPH Asia 2015

Global surface parametrization often requires the use of cuts or charts due to non-trivial topology. In recent years a focus has been on so-called seamless parametrizations, where the transition functions across the cuts are rigid transformations with a rotation about some multiple of 90 degrees. Of particular interest, e.g. for quadrilateral meshing, paneling, or texturing, are those instances where in addition the translational part of these transitions is integral (or more generally: quantized). We show that finding not even the optimal, but just an arbitrary valid quantization (one that does not imply parametric degeneracies), is a complex combinatorial problem. We present a novel method that allows us to solve it, i.e. to find valid as well as good quality quantizations. It is based on an original approach to quickly construct solutions to linear Diophantine equation systems, exploiting the specific geometric nature of the parametrization problem. We thereby largely outperform the state-of-the-art, sometimes by several orders of magnitude.


BendFields: Regularized Curvature Fields from Rough Concept Sketches

ACM Transactions on Graphics - 2015

Designers frequently draw curvature lines to convey bending of smooth surfaces in concept sketches. We present a method to extrapolate curvature lines in a rough concept sketch, recovering the intended 3D curvature field and surface normal at each pixel of the sketch. This 3D information allows to enrich the sketch with 3D-looking shading and texturing. We first introduce the concept of regularized curvature lines that model the lines designers draw over curved surfaces, encompassing curvature lines and their extension as geodesics over flat or umbilical regions. We build on this concept to define the orthogonal cross field that assigns two regularized curvature lines to each point of a 3D surface. Our algorithm first estimates the projection of this cross field in the drawing, which is nonorthogonal due to foreshortening. We formulate this estimation as a scattered interpolation of the strokes drawn in the sketch, which makes our method robust to sketchy lines that are typical for design sketches. Our interpolation relies on a novel smoothness energy that we derive from our definition of regularized curvature lines. Optimizing this energy subject to the stroke constraints produces a dense nonorthogonal 2D cross field which we then lift to 3D by imposing orthogonality. Thus, one central concept of our approach is the generalization of existing cross field algorithms to the nonorthogonal case. We demonstrate our algorithm on a variety of concept sketches with various levels of sketchiness. We also compare our approach with existing work that takes clean vector drawings as input.

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