Abstract Domain‐continuous visibility determination algorithms have proved to be very efficient at reducing noise otherwise prevalent in stochastic sampling. Even though they come with an increased overhead in terms of geometrical tests and visibility information management, their analytical nature provides such a rich integral that the pay‐off is often worth it. This paper presents a time‐continuous, primary visibility algorithm for motion blur aimed at ray tracing. Two novel intersection tests are derived and implemented. The first is for ray versus moving triangle and the second for ray versus moving AABB intersection. A novel take on shading is presented as well, where the time continuum of visible geometry is adaptively point‐sampled. Static geometry is handled using supplemental stochastic rays in order to reduce spatial aliasing. Finally, a prototype ray tracer with a full time‐continuous traversal kernel is presented in detail. The results are based on a variety of test scenarios and show that even though our time‐continuous algorithm has limitations, it outperforms multi‐jittered quasi‐Monte Carlo ray tracing in terms of image quality at equal rendering time, within wide sampling rate ranges.

Computing accurate visibility for thin primitives, such as hair strands, fur, grass, at all scales remains difficult or expensive. To that end, we present an efficient visibility algorithm based on spatial line sampling, and a novel intersection algorithm between line sample planes and Bézier splines with varying thickness. Our algorithm produces accurate visibility both when the projected width of the curve is a tiny fraction of a pixel, and when the projected width is tens of pixels. In addition, we present a rapid resolve procedure that computes final visibility. Using an optimized implementation running on graphics processors, we can render tens of thousands long hair strands with noise-free visibility at near-interactive rates.

We present a novel visibility algorithm for rendering motion blur with per-pixel anti-aliasing. Our algorithm uses a number of line samples over a rectangular group of pixels, and together with the time dimension, a two-dimensional spatio-temporal visibility problem needs to be solved per line sample. In a coarse culling step, our algorithm first uses a bounding volume hierarchy to rapidly remove geometry that does not overlap with the current line sample. For the remaining triangles, we approximate each triangle's depth function, along the line and along the time dimension, with a number of patch triangles. We resolve for the final color using an analytical visibility algorithm with depth sorting, simple occlusion culling, and clipping. Shading is decoupled from visibility, and we use a shading cache for efficient reuse of shaded values. In our results, we show practically noise-free renderings of motion blur with high-quality spatial anti-aliasing and with competitive rendering times. We also demonstrate that our algorithm, with some adjustments, can be used to accurately compute motion blurred ambient occlusion.