Research

Predictive Rendering

One of the main research areas within CGG is predictive rendering, the sub-discipline of computer graphics that attempts to provide reliable predictions of object appearance. In an industrial setting, this sort of capability is mainly needed for reliable virtual prototyping applications. Apart from a number of other technological keystones, requires accurate models of reflectance, as well as robust and unbiased simulations of light transport. Both these topics are active research areas within CGG, as well as the general research area of which physical effects have the capability of influencing object appearance sufficiently to warrant their simulation in a predictive renderer.

Robust and Efficient Light Transport Simulation

We focus on improving the robustness and efficiency of global illumination rendering. The goal is to design algorithms that can render environments with complex geometry, lighting, and materials in acceptable computation time. The main results in this area include our work on many-light rendering (Virtual Spherical Lights, Local & Global Lights, Effects of many-light rendering on material appearance, Importance Caching), robust photon mapping (BDPM, vertex merging), and caching approaches (SIGGRAPH 2008 Course, book, EGSR 2009 paper on Spatial-Directional caching). Also make sure to check out the SIGGRAPH 2010 course Global Illumination Across Industries.

Segmentation and visualization of medical volume data

We specialize in processing of data generated by medical tomographic scanners (CT, MRI). Currently we work on CT enterography data processing and segmentation of patological structures in liver and kidneys. We use modern GPGPU technologies (CUDA and OpenCL) - implementation of fast nonlocal means denoise, interactive segmentation based on watershed transformation, etc.