Computer Graphics is about digital models for threedimensional geometric objects as well as images. These shapes and images may represent approximations of the real world or could be synthetic, i.e., exist only in the computer. Goals of computer graphics research are the generation of plausible and informative images, and computation with reasonable resources, i.e. in a short amount of time with little storage requirements. The models and algorithms for this task combine knowledge from different areas of mathematics and computer science.
Panono’s panoramic camera, originally developed as a thesis work by CG alumnus Jonas Pfeil is now in it’s second revision and has been selected one of the 36 coolest gadgets in 2014 by CNN.
Prof. Alexa receives the Outstanding Technical Contributions Award of Eurographics. The award is “given each year to an individual in computer graphics to highlight some outstanding technical achievement.”
The award has been presented at the yearly main conference of Eurographics, which took place in Strasbourg, France this year.
Prominently featured in an episode of The Simpson was CG alumnus Andy Nealen’s game, Osmos: Milhouse had his iPad stolen on “The Simpsons.” When he finds it in Bart’s possession and begins to confront him, he is entranced by “the music of this bubble game.”
Jonas Pfeil, alumnus of the CG group, is turning his thesis work into a product: panono – a panoramic ball camera. Right now they are running a crowd-funding campaign on indiegogo and he appeared at TV Total, a popular late night talk show.
Prof. Alexa has been elected to the executive board of the Hybrid Plattform. He had been active in trans-disciplinary projects for years, strongly believing that this keeps science and research well-grounded.
Prof. Alexa had been elected to chair the technical program of SIGGRAPH 2013. SIGGRAPH regularly gathers thousands of scientists and professionals in the visual effects industry, and its technical program is the most prestigious and selective in the field. On the left, he opens the fast forward, a 30 second presentation for each of the accepted papers.
© Kristian Hildebrand
Most additive manufacturing technologies work by layering, i.e. slicing the shape and then generating each slice independently. This introduces an anisotropy into the process, often as different accuracies in the tangential and normal directions, but also in terms of other parameters such as build speed or tensile strength and strain. We model this as an anisotropic cubic element. Our approach then finds a compromise between modeling each part of the shape individually in the best possible direction and using one direction for the whole shape part. In particular, we compute an orthogonal basis and consider only the three basis vectors as slice normals (i.e. fabrication directions). Then we optimize a decomposition of the shape along this basis so that each part can be consistently sliced along one of the basis vectors.
In simulation, we show that this approach is superior to slicing the whole shape in one direction, only. It also has clear benefits if the shape is larger than the build volume of the available equipment.
The Dagstuhl seminar on ‘Computational Aspects of Fabrication’ organized by Alexa, Bickel, Matusik, McMains, Rushmeier has been accepted. More information here.
A radio feature about our recent research on sketch-based based modeling and sketch recognition on Deutschlandradio Kultur (German only): DRadio Kultur – Strichzeichnungen
- Scene assembled in a few minutes using our sketch-based retrieval system
- © Mathias Eitz
We develop a system for 3D object retrieval based on sketched feature lines as input. For objective evaluation, we collect a large number of query sketches from human users that are related to an existing data base of objects. The sketches turn out to be generally quite abstract with large local and global deviations from the original shape. Based on this observation, we decide to use a bag-of-features approach over computer generated line drawings of the objects. We develop a targeted feature transform based on Gabor filters for this system. We can show objectively that this transform is better suited than other approaches from the literature developed for similar tasks. Moreover, we demonstrate how to optimize the parameters of our, as well as other approaches, based on the gathered sketches. In the resulting comparison, our approach is significantly better than any other system described so far.
Please see our project page for more details.