@article{Wang2014374,
title = "Parallel and adaptive visibility sampling for rendering dynamic scenes with spatially varying reflectance ",
journal = "Computers & Graphics ",
volume = "38",
number = "0",
pages = "374 - 381",
year = "2014",
note = "",
issn = "0097-8493",
doi = "http://dx.doi.org/10.1016/j.cag.2013.10.036",
url = "http://www.sciencedirect.com/science/article/pii/S0097849313001775",
author = "Rui Wang and Minghao Pan and Xiang Han and Weifeng Chen and Hujun Bao",
keywords = "Adaptive visibility sampling",
keywords = "Environmental lighting",
keywords = "Dynamic scenes ",
abstract = "Abstract Fast rendering of dynamic scenes with natural illumination, all-frequency shadows and spatially varying reflections is important but challenging. One main difficulty brought by moving objects is that the runtime visibility update of dynamic occlusion is usually time-consuming and slow. In this paper, we present a new visibility sampling technique and show that efficient all-frequency rendering of dynamic scenes can be achieved by sampling visibility of dynamic objects in an adaptive and parallel way. First, we propose a two-level adaptive sampling scheme to distribute sample points spatially and compute visibility maps angularly on each sample point. Then, we present a parallel hemispherical distance transform to convert these visibility maps into spherical signed distance fields. Finally, using such a distance-based visibility representation, we integrate our visibility sampling algorithm in the all-frequency rendering framework for scenes with spatially varying BRDFs. With an entire GPU-based implementation, our algorithm enables interactive all-frequency rendering of moderate dynamic scenes with environment lighting and spatially varying reflectance. "
}