Research Projects

Realistic image synthesis is a key problem in computer graphics with numerous application areas, from digital entertainment to architecture and industrial design. The goal of most previous rendering algorithms is to converge to the ground truth solution as quickly as possible with increasing computation time, stopping when the desired quality criteria are met. In contrast, in this project we consider the problem to obtain the best possible approximate solution under a given time constraint. A key idea is to achieve this by modifying the rendering problem at hand, i.e. the light transport simulation and image reconstruction, using mollification.

Setting up a visual inspection station (e.g. for industrial production) is a non-trivial task and usually done manually by field experts. The goal of this project is to use computer graphics in an expert-guided system to optimally setup the inspection station, e.g. light source and sensor positions with regard to the given inspection task and the algorithms used. Computer graphics is used to render representations of the scene as the sensor would sense it. This output is then used in an optimization system to evaluate a possible setup. Additionally the rendering process can generate additional data not available to a sensor to guide the optimization process. More information can be found here.

In this project we work on rendering and display algorithms for large-scale stereoscopic high dynamic range projections. We evaluate our algorithms using a scaled prototype of our reflective HDR display. More information can be found here.

In this project, carried out together with Weta Digital (one of the world’s premier visual effects companies) we work on photorealistic rendering algorithms.

This project is funded by the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB) and investigates the use of predictive rendering and procedurally modeled objects to simulate optical inspection systems and train image processing algorithms.

This project addresses the challenges that arise in the visualization of large multivariate and time-dependent volume data sets, such as resulting from evergrowing scientific simulations in many fields, ranging from astrophysics to bioinformatics. Not only does the sheer amount of data require highly efficient methods for the visualization of such data sets. Moreover, finding visualizations that allow for insightful exploration of highly multivariate and time-dependent data sets is a difficult undertaking: The dimensionality of human perception is severely limited, demanding for crafted projections of high-dimensional data that reduce the information to a perceivable amount, while retaining context and meaning. Therefore, fast and targeted visualizations that allow for a connected inspection of different views and projections are key to successfully analyzing and understanding such data. In order to maintain the right focus, the project is steered by collaboration with scientific domain experts from HITS and KIT. 

This project focuses on the challenges of radiative transport simulation and the visualization of the simulation results in the context of astrophysics.

In the Helmholtz program "Super Computing and Big Data" (Topic 2: Data-Intensive Science and Federated Computing) the Visualization Lab bundles the competences in scientific visualization and communicates with scientific communities at KIT, and develops novel scalable visualization techniques.

A cooperation with HITS, HLRS, Uni Freiburg and Universität Heidelberg. The project aims to find alternative ways to video streaming for remote visualization of scientific data with custom visualization pipeline decomposition and task distribution.

The IVCI funded research in efficient light transport simulation (among others: with discrete ordinate methods), and analysis and manipulation of light transport for artistic applications.