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.
We welcome Daniel Archambault to Swansea. Daniel has joined us as a permanent lecturer in the area of Visualization.
Today, James Walker successfully defended his MRes Thesis:
Visualization of Large, High-Dimensional, Time-Dependent, Abstract Data.
Well done James and Bob (supervisor). The internal examiner was Ben Mora and the external was Yulia Hicks (Cardiff).
Today Zhao Geng successfully defended his PhD titled Visual Analysis of Abstract, Multi-Dimensional Data with Parallel Coordinates. Well done Zhao and Bob (supervisor). The internal examiner was Rita Borgo and the external was David Duce (Oxford Brookes).
New RIVIC funded lecturer Gary Tam starts today in his first permanent academic post.
We’re really happy that Eurovis 2014 will be held in Swansea, hosted by the Visual Computing group.
In written and spoken communications, figures of speech (e.g., metaphors and synecdoche) are often used as an aid to help convey abstract or less tangible concepts. However, the benefits of using rhetorical illustrations or embellishments in visualization have so far been inconclusive. In this work, we report an empirical study to evaluate hypotheses that visual embellishments may aid memorization, visual search and concept comprehension. One major departure from related experiments in the literature is that we make use of a dualtask methodology in our experiment. This design offers an abstraction of typical situations where viewers do not have their full attention focused on visualization (e.g., in meetings and lectures). The secondary task introduces “divided attention”, and makes the effects of visual embellishments more observable. In addition, it also serves as additional masking in memory-based trials. The results of this study show that visual embellishments can help participants better remember the information depicted in visualization. On the other hand, visual embellishments can have a negative impact on the speed of visual search. The results show a complex pattern as to the benefits of visual embellishments in helping participants grasp key concepts from visualization.
Joel Dearden and Aris Tsitiridis starts working here as a RIVIC RAs with Mark W. Jones and Ben Mora today.
The Expectation Maximization (EM) algorithm is an alternative reconstruction method to the Filtered Back Projection method, providing many advantages including decreased sensitivity to noise. However the algorithm requires a large number of iterations to reach adequate convergence. Due to this, research has been carried out into accelerating the convergence rate of the EM algorithm. In this paper we present an analysis of an EM implementation which uses both OSEM and MGEM, comparing results on a per time basis with both acceleration techniques alone as well as a combination of the two methods. We provide an alternative stopping criterion based on the RMS error of the projections of the current reconstruction and compare the result with an existing variance based approach.