Abstract:In this paper, we introduce coverage-based opacity estimation to achieve Depth of Field (DoF) effects when visualizing molec- ular dynamics (MD) data. The proposed algorithm is a novel object-based approach which eliminates many of the shortcom- ings of state-of-the-art image-based DoF algorithms. Based on observations derived from a physically-correct reference renderer, coverage-based opacity estimation exploits semi-transparency to simulate the blur inherent to DoF effects. It achieves high qual- ity DoF effects, by augmenting each atom with a semi-transparent shell, which has a radius proportional to the distance from the fo- cal plane of the camera. Thus, each shell represents an additional coverage area whose opacity varies radially, based on our observa- tions derived from the results of multi-sampling DoF algorithms. By using the proposed technique, it becomes possible to generate high quality visual results, comparable to those achieved through ground-truth multi-sampling algorithms. At the same time, we ob- tain a significant speedup which is essential for visualizing MD data as it enables interactive rendering. In this paper, we derive the un- derlying theory, introduce coverage-based opacity estimation and demonstrate how it can be applied to real world MD data in or- der to achieve DoF effects. We further analyze the achieved results with respect to performance as well as quality and show that they are comparable to images generated with modern distributed ray tracing engines.