Today we took delivery of our new Xeon Phi machine. We have 4 Xeon Phis and 2 Xeon 12 core CPUs making 260 cores in this single PC chassis. Ben Mora will supervise 2 new PhD students working on Physics problems and techniques with this machine. Mark W. Jones will also have a new PhD student that will be able to exploit this machine for ray tracing. Generally the machine will be used throughout the group as a platform for parallel computation using the new Intel MIC architecture.
This equipment was funded by the Welsh Government through RIVIC.
Path traced, 16 samples using Probabilistic illumination-aware filtering
Noise removal for Monte Carlo global illumination rendering is a well known problem, and has seen significant attention from image-based filtering methods. However, many state of the art methods breakdown in the presence of high frequency features, complex lighting and materials. In this work we present a probabilistic image based noise removal and irradiance filtering framework that preserves this high frequency detail such as hard shadows and glossy reflections, and imposes no restrictions on the characteristics of the light transport or materials. We maintain per-pixel clusters of the path traced samples and, using statistics from these clusters, derive an illumination aware filtering scheme based on the discrete Poisson probability distribution. Furthermore, we filter the incident radiance of the samples, allowing us to preserve and filter across high frequency and complex textures without limiting the effectiveness of the filter.
Ian C. Doidge and Mark W. Jones.
CGI 2013, The Visual Computer 29(6-8),707-616, 2013. The final publication is available at www.springerlink.com.
We are pleased to announce our award of Best Paper at Eurographics 2013 for our paper Photon Parameterisation for Robust Relaxation Constraints, Ben Spencer and Mark W. Jones. [Link to paper]
The paper introduces a technique that augments each photon with information about its origin trajectory. Using this, lighting is separable during density estimation queries. Additionally, we spot fine edge detail using PCA allowing us to employ photon relaxation without detrimental effects. This results in high qualify photon maps that reduce variance and can be rendered with very low bandwidth kernels reducing bias. [Link to news on EG.org]
This paper presents a novel approach to detecting and preserving fine illumination structure within photon maps. Data derived from each photon’s primal trajectory is encoded and used to build a high-dimensional kd-tree. Incorporation of these new parameters allows for precise differentiation between intersecting ray envelopes, thus minimizing detail degradation when combined with photon relaxation. We demonstrate how parameter-aware querying is beneficial in both detecting and removing noise. We also propose a more robust structure descriptor based on principal components analysis that better identifies anisotropic detail at the sub-kernel level.We illustrate the effectiveness of our approach in several example scenes and show significant improvements when rendering complex caustics compared to previous methods.
Ben Spencer and Mark W. Jones
Computer Graphics Forum, Volume 32, Issue 2pt1, pages 83–92, May 2013. [doi]
Best paper, Eurographics 2013.
Researchers from Swansea, Cardiff, Aberystwyth and Bangor all attended the 2013 RIVIC graduate school in Bangor and Portmeirion 10th-11th April. Portmeirion was a great setting for the conference – we took over all of the village and some of the castle. We had lots of great talks from PhD students, researchers, lecturers and guest speakers of Hans-Peter Seidel and Min Chen.
Stream compaction is an important parallel computing primitive that produces a reduced (compacted) output stream consisting of only valid elements from an input stream containing both invalid and valid elements. Computing on this compacted stream rather than the mixed input stream leads to improvements in performance, load balancing, and memory footprint. Stream compaction has numerous applications in a wide range of domains: e.g., deferred shading, isosurface extraction, and surface voxelization in computer graphics and visualization. We present a novel In-Kernel stream compaction method, where compaction is completed before leaving an operating kernel. This contrasts with conventional parallel compaction methods that require leaving the kernel and running a prefix sum kernel followed by a scatter kernel. We apply our compaction methods to ray-tracing-based visualization of volumetric data. We demonstrate that the proposed In-Kernel Compaction outperforms the standard out-of-kernel Thrust parallel-scan method for performing stream compaction in this real-world application. For the data visualization, we also propose a novel multi-kernel ray-tracing pipeline for increased thread coherency and show that it outperforms a conventional single-kernel approach.
D. M. Hughes, I. S. Lim, M. W. Jones, A. Knoll and B. Spencer
Computer Graphics Forum, 2013, 32(6), 178-188. [doi]
Winning image for Computer Graphics Forum cover competition 2013
Ben Spencer and Mark W. Jones have again won the Computer Graphics Forum cover competition. The winning image will be used throughout 2013 as the front cover image of the journal Computer Graphics Forum. The image shows a visualisation of the parameter space of photon trajectory from the emitting light source. When encoded into the photon map, this can be used to distinguish overlapping light envelopes typically associated with caustics. This enables more accurate density estimation along overlapping illumination, thus producing more accurate renders. The technique is described in an upcoming Eurographics 2013 paper. See their previous prize winning entry for 2009.
We introduce a novel algorithm for progressively removing noise from view-independent photon maps while simultaneously minimizing residual bias. Our method refines a primal set of photons using data from multiple successive passes to estimate the incident flux local to each photon. We show how this information can be used to guide a relaxation step with the goal of enforcing a constant, per-photon flux. Using a reformulation of the radiance estimate, we demonstrate how the resulting blue noise photon distribution yields a radiance reconstruction in which error is significantly reduced. Our approach has an open-ended runtime of the same order as unbiased and asymptotically consistent rendering methods, converging over time to a stable result. We demonstrate its effectiveness at storing caustic illumination within a view-independent framework and at a fidelity visually comparable to reference images rendered using progressive photon mapping.
Ben Spencer and Mark W. Jones
ACM Transactions on Graphics. 32(1), January 2013 [doi] [bibtex]
We welcome Daniel Archambault to Swansea. Daniel has joined us as a permanent lecturer in the area of Visualization.