The Visible Differences Predictor: applications to global illumination problems

Abstract

In this study of global illumination computations, we investigatethe applications of the perceptually-based Visual Difference Predictor(VDP) developed by Daly. First, we validate the performance of thispredictor in shadow masking by texture and luminance contrast experiments.We also experiment with Contrast Sensitivity Functions (CSFs) derivedfrom the results of various psychophysical experiments, various spatialfrequency and orientation channel decomposition schemes, and contrastdefinitions, in order to check predictor integrity and sensitivityto differing models of visual mechanisms. We show applications ofthe VDP to monitor the perceived quality of the progressive radiosityand Monte Carlo solutions, and decide upon their stopping conditions.Also, based on the local error metric provided by the predictor weshow some initial attempts to drive adaptive mesh subdivision inradiosity computations.