Jaakko Lehtinen

Temporal light field reconstruction for rendering distribution effects

Traditionally, effects that require evaluating multidimensional integrals for each pixel, such as motion blur, depth of field, and soft shadows, suffer from noise due to the variance of the high-dimensional integrand. In this paper, we describe a general reconstruction technique that exploits the anisotropy in the temporal light field and permits efficient reuse of samples between pixels, multiplying the effective sampling rate by a large factor. We show that our technique can be applied in situations that are challenging or impossible for previous anisotropic reconstruction methods, and that it can yield good results with very sparse inputs. We demonstrate our method for simultaneous motion blur, depth of field, and soft shadows.

Decoupled sampling for graphics pipelines

We propose a generalized approach to decoupling shading from visibility sampling in graphics pipelines, which we call decoupled sampling. Decoupled sampling enables stochastic supersampling of motion and defocus blur at reduced shading cost, as well as controllable or adaptive shading rates which trade off shading quality for performance. It can be thought of as a generalization of multisample antialiasing (MSAA) to support complex and dynamic mappings from visibility to shading samples, as introduced by motion and defocus blur and adaptive shading. It works by defining a many-to-one hash from visibility to shading samples, and using a buffer to memoize shading samples and exploit reuse across visibility samples. Decoupled sampling is inspired by the Reyes rendering architecture, but like traditional graphics pipelines, it shades fragments rather than micropolygon vertices, decoupling shading from the geometry sampling rate. Also unlike Reyes, decoupled sampling only shades fragments after precise computation of visibility, reducing overshading.n We present extensions of two modern graphics pipelines to support decoupled sampling: a GPU-style sort-last fragment architecture, and a Larrabee-style sort-middle pipeline. We study the architectural implications of decoupled sampling and blur, and derive end-to-end performance estimates on real applications through an instrumented functional simulator. We demonstrate high-quality motion and defocus blur, as well as variable and adaptive shading rates.

Sketching Clothoid Splines Using Shortest Paths

Clothoid splines are gaining popularity as a curve representation due to their intrinsically pleasing curvature, which varies piecewise linearly over arc length. However, constructing them from hand‐drawn strokes remains difficult. Building on recent results, we describe a novel algorithm for approximating a sketched stroke with a fair (i.e., visually pleasing) clothoid spline. Fairness depends on proper segmentation of the stroke into curve primitives — lines, arcs, and clothoids. Our main idea is to cast the segmentation as a shortest path problem on a carefully constructed weighted graph. The nodes in our graph correspond to a vastly overcomplete set of curve primitives that are fit to every subsegment of the sketch, and edges correspond to transitions of a specified degree of continuity between curve primitives. The shortest path in the graph corresponds to a desirable segmentation of the input curve. Once the segmentation is found, the primitives are fit to the curve using non‐linear constrained optimization. We demonstrate that the curves produced by our method have good curvature profiles, while staying close to the user sketch.

Reconstructing the indirect light field for global illumination

Stochastic techniques for rendering indirect illumination suffer from noise due to the variance in the integrand. In this paper, we describe a general reconstruction technique that exploits anisotropy in the light field and permits efficient reuse of input samples between pixels or world-space locations, multiplying the effective sampling rate by a large factor. Our technique introduces visibility-aware anisotropic reconstruction to indirect illumination, ambient occlusion and glossy reflections. It operates on point samples without knowledge of the scene, and can thus be seen as an advanced image filter. Our results show dramatic improvement in image quality while using very sparse input samplings.

Clipless dual-space bounds for faster stochastic rasterization

We present a novel method for increasing the efficiency of stochastic rasterization of motion and defocus blur. Contrary to earlier approaches, our method is efficient even with the low sampling densities commonly encountered in realtime rendering, while allowing the use of arbitrary sampling patterns for maximal image quality. Our clipless dual-space formulation avoids problems with triangles that cross the camera plane during the shutter interval. The method is also simple to plug into existing rendering systems.

A hierarchical volumetric shadow algorithm for single scattering

Volumetric effects such as beams of light through participating media are an important component in the appearance of the natural world. Many such effects can be faithfully modeled by a single scattering medium. In the presence of shadows, rendering these effects can be prohibitively expensive: current algorithms are based on ray marching, i.e., integrating the illumination scattered towards the camera along each view ray, modulated by visibility to the light source at each sample. Visibility must be determined for each sample using shadow rays or shadow-map lookups. We observe that in a suitably chosen coordinate system, the visibility function has a regular structure that we can exploit for significant acceleration compared to brute force sampling. We propose an efficient algorithm based on partial sum trees for computing the scattering integrals in a single-scattering homogeneous medium. On a CPU, we achieve speedups of 17--120x over ray marching.

Occluder Simplification Using Planar Sections

We present a method for extreme occluder simplification. We take a triangle soup as input, and produce a small set of polygons with closely matching occlusion properties. In contrast to methods that optimize the original geometry, our algorithm has very few requirements for the input— specifically, the input does not need to be a watertight, two‐manifold mesh. This robustness is achieved by working on a well‐behaved, discretized representation of the input instead of the original, potentially badly structured geometry. We first formulate the algorithm for individual occluders, and further introduce a hierarchy for handling large, complex scenes.

Sequential Monte Carlo Instant Radiosity

Instant Radiosity and its derivatives are interactive methods for efficiently estimating global (indirect) illumination. They represent the last indirect bounce of illumination before the camera as the composite radiance field emitted by a set of virtual point light sources (VPLs). In complex scenes, current algorithms suffer from a difficult combination of two issues: it remains a challenge to distribute VPLs in a manner that simultaneously gives a high-quality indirect illumination solution for each frame, and to do so in a temporally coherent manner. We address both issues by building, and maintaining over time, an adaptive and temporally coherent distribution of VPLs in locations where they bring indirect light to the image. We introduce a novel heuristic sampling method that strives to only move as few of the VPLs between frames as possible. The result is, to the best of our knowledge, the first interactive global illumination algorithm that works in complex, highly-occluded scenes, suffers little from temporal flickering, supports moving cameras and light sources, and is output-sensitive in the sense that it places VPLs in locations that matter most to the final result.