Partitioned Shadow Volumes

Real-time shadows remain a challenging problem in computer graphics. In this context, shadow algorithms generally rely either on shadow mapping or shadow volumes. This paper rediscovers an old class of algorithms that build a binary space partition over the shadow volumes. For almost 20 years, such methods have received little attention as they have been considered lacking of both robustness and efficiency. We show that these issues can be overcome, leading to a simple and robust shadow algorithm. Hence we demonstrate that this kind of approach can reach a high level of performance. Our algorithm uses a new partitioning strategy which avoids any polygon clipping. It relies on a Ternary Object Partitioning tree, a new data structure used to find if an image point is shadowed. Our method works on a triangle soup and its memory footprint is fixed. Our experiments show that it is efficient and robust, including for finely tessellated models.