Towards Predictive Rendering in Virtual Reality

Radiometrically correct images are extremely important for Virtual Reality applications like Virtual Design, where users need to make decisions impacting large investments based on simulations. Unfortunately, generation of such imagery is still an unsolved problem due to manifold reasons. First, rendered scenes are not modeled accurately enough. Second, even with huge computational efforts existing rendering algorithms lack sufficient precision. Third, current display devices convert rendered images into low-dimensional color spaces, which prohibits display of radiometrically correct results. Overcoming these limitations is the focus of current state-of-the-art research. This thesis also contributes to this task. First, it briefly introduces the necessary background and identifies the steps required for real-time predictive image generation. Then, existing techniques targeting these steps are presented. To solve some of the remaining problems, novel techniques are proposed. They cover various steps in the predictive image generation process, ranging from accurate scene modeling over efficient data representation to high-quality, real-time rendering.