Aggressive region-based visibility computation using importance sampling

We present an aggressive region-based visibility sampling algorithm for general 3D scenes. The visibility portal in the scene is a cue for guiding the visibility sampling. Our algorithm extends the image space sampling algorithm by measuring the size and orientation of portals in the scene, and results in a predictable sampling mechanism of visible set in the image space. An importance visibility sampling scheme in the image space is proposed based on the visibility portals, and used to guide the sampling process. Each newly added visibility sample is placed at the position potentially visible for most missing polygons. Experiments show that our sampling approach can effectively improve the performance of visibility sampling in both the convergence rate and the visual quality compared to the previous approaches.