A Framework for the Generation of Textures Representing Time-Dependent Changes in the Appearance of Dust Layers

Abstract

The perception of realism in computer generated images can be significantly enhanced by subtle visual cues. Among those, one can highlight the presence of dust on synthetic objects, which is often subject to temporal variations in real settings. Moreover, by re- alistically depicting the appearance of dust accumulated over time, one can also convey subtle information about the history of a scene. In this thesis, we present a framework for the generation of textures representing the accumulation of this ubiquitous material over time in indoor settings. It employs a physically-inspired approach to portray the effects of different levels of accumulated dust roughness on the appearance of substrate surfaces, and to modulate these effects according to the different illumination and viewing geometries. The development of its core algorithms was guided by empirical insights and data obtained from observational experiments which are also described. To illustrate its applicability to the rendering of visually plausible depictions of time-dependent changes in dusty scenes, we provide sequences of images obtained considering distinct dust accumulation scenarios.