Tomáš Davidovič

Light transport simulation with vertex connection and merging

Developing robust light transport simulation algorithms that are capable of dealing with arbitrary input scenes remains an elusive challenge. Although efficient global illumination algorithms exist, an acceptable approximation error in a reasonable amount of time is usually only achieved for specific types of input scenes. To address this problem, we present a reformulation of photon mapping as a bidirectional path sampling technique for Monte Carlo light transport simulation. The benefit of our new formulation is twofold. First, it makes it possible, for the first time, to explain in a formal manner the relative efficiency of photon mapping and bidirectional path tracing, which have so far been considered conceptually incompatible solutions to the light transport problem. Second, it allows for a seamless integration of the two methods into a more robust combined rendering algorithm via multiple importance sampling. A progressive version of this algorithm is consistent and efficiently handles a wide variety of lighting conditions, ranging from direct illumination, diffuse and glossy inter-reflections, to specular-diffuse-specular light transport. Our analysis shows that this algorithm inherits the high asymptotic performance from bidirectional path tracing for most light path types, while benefiting from the efficiency of photon mapping for specular-diffuse-specular lighting effects.

Efficient stack-less BVH traversal for ray tracing

We propose a new, completely iterative traversal algorithm for ray tracing bounding volume hierarchies that is based on storing a parent pointer with each node, and on using simple state logic to infer which node to traverse next. Though our traversal algorithm does re-visit internal nodes, it intersects each visited node only once, and in general performs exactly the same ray-box tests and ray-primitive intersection tests---and in exactly the same order---as a traditional stack-based variant. The proposed algorithm can be used for computer architectures that need to minimize the use of local memory for processing rays or those that need to minimize the data transport such as distributed multi-CPU architectures.

Combining global and local virtual lights for detailed glossy illumination

Accurately rendering glossy materials in design applications, where previewing and interactivity are important, remains a major challenge. While many fast global illumination solutions have been proposed, all of them work under limiting assumptions on the materials and lighting in the scene. In the presence of many glossy (directionally scattering) materials, fast solutions either fail or degenerate to inefficient, brute-force simulations of the underlying light transport. In particular, many-light algorithms are able to provide fast approximations by clamping elements of the light transport matrix, but they eliminate the part of the transport that contributes to accurate glossy appearance. In this paper we introduce a solution that separately solves for the global (low-rank, dense) and local (highrank, sparse) illumination components. For the low-rank component we introduce visibility clustering and approximation, while for the high-rank component we introduce a local light technique to correct for the missing illumination. Compared to competing techniques we achieve superior gloss rendering in minutes, making our technique suitable for applications such as industrial design and architecture, where material appearance is critical.

Progressive Light Transport Simulation on the GPU: Survey and Improvements

Graphics Processing Units (GPUs) recently became general enough to enable implementation of a variety of light transport algorithms. However, the efficiency of these GPU implementations has received relatively little attention in the research literature and no systematic study on the topic exists to date. The goal of our work is to fill this gap. Our main contribution is a comprehensive and in-depth investigation of the efficiency of the GPU implementation of a number of classic as well as more recent progressive light transport simulation algorithms. We present several improvements over the state-of-the-art. In particular, our light vertex cache, a new approach to mapping connections of subpath vertices in bidirectional path tracing on the GPU, outperforms the existing implementations by 30--60%. We also describe a first GPU implementation of the recently introduced vertex connection and merging algorithm [Georgiev et al. 2012], showing that even relatively complex light transport algorithms can be efficiently mapped on the GPU. With the implementation of many of the state-of-the-art algorithms within a single system at our disposal, we present a unique direct comparison and analysis of their relative performance.

Progressive Stochastic Reconstruction Technique (PSRT) for cryo electron tomography.

Cryo Electron Tomography (cryoET) plays an essential role in Structural Biology, as it is the only technique that allows to study the structure of large macromolecular complexes in their close to native environment in situ. The reconstruction methods currently in use, such as Weighted Back Projection (WBP) or Simultaneous Iterative Reconstruction Technique (SIRT), deliver noisy and low-contrast reconstructions, which complicates the application of high-resolution protocols, such as Subtomogram Averaging (SA). We propose a Progressive Stochastic Reconstruction Technique (PSRT) - a novel iterative approach to tomographic reconstruction in cryoET based on Monte Carlo random walks guided by Metropolis-Hastings sampling strategy. We design a progressive reconstruction scheme to suit the conditions present in cryoET and apply it successfully to reconstructions of macromolecular complexes from both synthetic and experimental datasets. We show how to integrate PSRT into SA, where it provides an elegant solution to the region-of-interest problem and delivers high-contrast reconstructions that significantly improve template-based localization without any loss of high-resolution structural information. Furthermore, the locality of SA is exploited to design an importance sampling scheme which significantly speeds up the otherwise slow Monte Carlo approach. Finally, we design a new memory efficient solution for the specimen-level interior problem of cryoET, removing all associated artifacts.

Manuka: A Batch-Shading Architecture for Spectral Path Tracing in Movie Production

The Manuka rendering architecture has been designed in the spirit of the classic reyes rendering architecture: to enable the creation of visually rich computer generated imagery for visual effects in movie production. Following in the footsteps of reyes over the past 30 years, this means supporting extremely complex geometry, texturing, and shading. In the current generation of renderers, it is essential to support very accurate global illumination as a means to naturally tie together different assets in a picture. This is commonly achieved with Monte Carlo path tracing, using a paradigm often called shade on hit, in which the renderer alternates tracing rays with running shaders on the various ray hits. The shaders take the role of generating the inputs of the local material structure, which is then used by path-sampling logic to evaluate contributions and to inform what further rays to cast through the scene. We propose a shade before hit paradigm instead and minimise I/O strain on the system, leveraging locality of reference by running pattern generation shaders before we execute light transport simulation by path sampling. We describe a full architecture built around this approach, featuring spectral light transport and a flexible implementation of multiple importance sampling (mis), resulting in a system able to support a comparable amount of extensibility to what made the reyes rendering architecture successful over many decades.

PSRT: Progressive Stochastic Reconstruction Technique for Cryo Electron Tomography

Cryo Electron Tomography (cryoET) is one of the essential techniques in Structural Biology, as it allows us to study the structure of macromolecular complexes in their native environment in situ. The tomographic reconstruction in cryoET is a particularly challenging task as the input data suffers from very low contrast, high noise, and limited tilt range. Moreover, the scanned specimen is larger than the detector, introducing the interior problem into the reconstruction process, which causes vignetting artifacts on the edges of the reconstructions. To alleviate some of these limitations, high-resolution protocols such as Subtomogram Averaging (SA) are applied to obtain structures of individual macromolecular complexes from a tomogram. Results of these protocols are highly dependent on the quality of the reconstruction. Current state-of-the-art methods such as Weighted Back Projection (WBP) or Simultaneous Algebraic Reconstruction Technique (SART) deliver noisy and low-contrast reconstructions and thus manual intervention is often needed during SA.

Progressive stochastic reconstruction technique for cryo electron tomography

Cryo Electron Tomography (cryoET) plays an essential role in Structural Biology, as it is the only technique that allows to study the structure and intracellular distribution of large macromolecular complexes in their (close to) native environment. A major limitation of cryoET is the highest achievable resolution, currently at around 3 nm, which prevents its application to smaller complexes and in turn to a wider range of important biological questions.