Peter-Pike J. Sloan

Fast and Efficient Skinning of Animated Meshes

Skinning is a simple yet popular deformation technique combining compact storage with efficient hardware accelerated rendering. While skinned meshes (such as virtual characters) are traditionally created by artists, previous work proposes algorithms to construct skinning automatically from a given vertex animation. However, these methods typically perform well only for a certain class of input sequences and often require long pre‐processing times. We present an algorithm based on iterative coordinate descent optimization which handles arbitrary animations and produces more accurate approximations than previous techniques, while using only standard linear skinning without any modifications or extensions. To overcome the computational complexity associated with the iterative optimization, we work in a suitable linear subspace (obtained by quick approximate dimensionality reduction) and take advantage of the typically very sparse vertex weights. As a result, our method requires about one or two orders of magnitude less pre‐processing time than previous methods.

Physics-inspired upsampling for cloth simulation in games

We propose a method for learning linear upsampling operators for physically-based cloth simulation, allowing us to enrich coarse meshes with mid-scale details in minimal time and memory budgets, as required in computer games. In contrast to classical subdivision schemes, our operators adapt to a specific context (e.g. a flag flapping in the wind or a skirt worn by a character), which allows them to achieve higher detail. Our method starts by pre-computing a pair of coarse and fine training simulations aligned with tracking constraints using harmonic test functions. Next, we train the upsampling operators with a new regularization method that enables us to learn mid-scale details without overfitting. We demonstrate generalizability to unseen conditions such as different wind velocities or novel character motions. Finally, we discuss how to re-introduce high frequency details not explainable by the coarse mesh alone using oscillatory modes.

Progressive photon beams

We present progressive photon beams, a new algorithm for rendering complex lighting in participating media. Our technique is efficient, robust to complex light paths, and handles heterogeneous media and anisotropic scattering while provably converging to the correct solution using a bounded memory footprint. We achieve this by extending the recent photon beams variant of volumetric photon mapping. We show how to formulate a progressive radiance estimate using photon beams, providing the convergence guarantees and bounded memory usage of progressive photon mapping. Progressive photon beams can robustly handle situations that are difficult for most other algorithms, such as scenes containing participating media and specular interfaces, with realistic light sources completely enclosed by refractive and reflective materials. Our technique handles heterogeneous media and also trivially supports stochastic effects such as depth-of-field and glossy materials. Finally, we show how progressive photon beams can be implemented efficiently on the GPU as a splatting operation, making it applicable to interactive and real-time applications. These features make our technique scalable, providing the same physically-based algorithm for interactive feedback and reference-quality, unbiased solutions.

Volumetric obscurance

Obscurance and Ambient Occlusion (AO) are popular techniques in both film and games that model how ambient light is shadowed. While it is largely a solved problem for static scenes, for dynamic scenes it is still difficult to compute at interactive rates. Recent attempts to compute AO in screen space for dynamic scenes either have poor performance or suffer from under-sampling problems. We formulate the problem as a 3D volumetric integral, which maps more naturally to graphics hardware. This integral can be solved using line samples to improve the under-sampling problems that plague other techniques. Following the idea of line integrals to its logical conclusion, we show results using area samples that use a simple statistical model of the depth buffer that allows us to use a single sample. We also discuss strategies for generating point, line, and area sample patterns along with ways to incorporate the surface normal into the volume obscurance calculation.

Least squares vertex baking

We investigate the representation of signals defined on triangle meshes using linearly interpolated vertex attributes. Compared to texture mapping, storing data only at vertices yields significantly lower memory overhead and less expensive runtime reconstruction. However, standard approaches to determine vertex values such as point sampling or averaging triangle samples lead to suboptimal approximations. We discuss how an optimal solution can be efficiently calculated using continuous least‐squares. In addition, we propose a regularization term that allows us to minimize gradient discontinuities and mach banding artifacts while staying close to the optimum. Our method has been integrated in a game production lighting tool and we present examples of representing signals such as ambient occlusion and precomputed radiance transfer in real game scenes, where vertex baking was used to free up resources for other game components.

Enhancements to Model-reduced Fluid Simulation

We present several enhancements to model-reduced fluid simulation that allow improved simulation bases and two-way solid-fluid coupling. Specifically, we present a basis enrichment scheme that allows us to combine data driven or artistically derived bases with more general analytic bases derived from Laplacian Eigenfunctions. We handle two-way solid-fluid coupling in a time-splitting fashion---we alternately timestep the fluid and rigid body simulators, while taking into account the effects of the fluid on the rigid bodies and vice versa. We employ the vortex panel method to handle solid-fluid coupling and use dynamic pressure to compute the effect of the fluid on rigid bodies.

Runtime implementation of modular radiance transfer

Real-time rendering of indirect lighting significantly enhances the sense of realism in video games. Unfortunately, previously including such effects often required time consuming scene dependent precomputation and heavy runtime computations unsuitable for low-end devices, such as mobile phones or game consoles. Modular Radiance Transfer (MRT) [Loos et al. 2011] is a recent technique that computes approximate direct-to-indirect transfer [Hašan et al. 2006; Kontkanen et al. 2006; Lehtinen et al. 2008] by warping and combining light transport, in real-time, from a small library of simple shapes. This talk focusses on implementation issues of the MRT technical paper, including how our run time is designed to scale across many different platforms, from iPhones to modern GPUs.

Irradiance rigs

When precomputed lighting is generated for static scene elements, the incident illumination on dynamic objects must be computed in a manner that is efficient and that faithfully captures the near- and far-field variation of the environments illumination. Depending on the relative size of dynamic objects, as well as the number of lights in the scene, previous approaches fail to adequately sample the incident lighting and/or fail to scale. We present a principled, error-driven approach for dynamically transitioning between near- and far-field lighting. A more accurate model for sampling near-field lighting for disk sources is introduced, as well as far-field sampling and interpolation schemes tailored to each dynamic object. Lastly, we apply a flexible reflectance model to the computed illumination.

Normal Mapping with Low-Frequency Precomputed Visibility

Abstract Normal mapping is a common technique used in video games, decoupling surface details stored at high spatial frequencies, which are often tiled or repeated, from lighting information that is both unique and stored at a lower sampling rate. This paper presents two techniques that couple normal maps on static geometry with soft shadows from smooth distant lighting in a more efficient manner compared with previous work. In the first technique, the visibility function is represented using low-order spherical harmonics, and the product of the Lambertian-clamped cosine function and the lighting environment is tabulated in textures. The second technique uses principal component analysis to compress the visibility function, decreasing the data size and increasing the performance. Finally, we also examine the efficiency of four common parameterizations for spherical harmonics.

Normal mapping with low-frequency precomputed visibility

Normal mapping, ubiquitous in video games, decouples details stored at high spatial frequencies, often tiled or repeated, from unique lighting information stored at a lower sampling rates. Our technique enables normal maps on static geometry to interact with soft shadows from smooth distant lighting more efficiently compared to previous work. The visibility function is represented using low-order spherical harmonics, and the product of the cosine function and the lighting environment is tabulated in textures, decoupling normal variation from visibility. PCA compresses the results and accelerate the computation.