Perception-based global illumination, rendering, and animation techniques

In this paper, we consider applications of perception-based video quality metrics to improve the performance of global lighting computations and rendering of anima-tion sequences. To control the computation of anima-tion frames we use the Animation Quality Metric (AQM) which is an extended version of the Visible Difference Pre-dictor (VDP) developed by Daly. We show two applica-tions of the AQM: (1) the rendering of high-quality walk-throughs for static environments and (2) the computation of global illumination for dynamic environments. To improve the rendering performance of our walk-through solution we use a hybrid of the ray tracing and Image-Based Rendering (IBR) techniques. In our render-ing solution we derive as many pixels as possible using inexpensive IBR techniques without affecting the anima-tion quality. The AQM is used to automatically guide such a hybrid rendering. Also, we present a method for efficient global illumi-nation computation in dynamic environments by taking advantage of temporal coherence of lighting distribution. The method is embedded in the framework of stochas-tic photon tracing and density estimation techniques. The AQM is used to keep noise inherent in stochastic methods below the sensitivity level of the human observer. As a re-sult a perceptually-consistent quality across all animation frames is obtained. Furthermore, the computation cost is reduced compared to the traditional approaches operating solely in the spatial domain