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.
Welcome to Mr. Robert Palmer who started his PhD in Medical Image Analysis under the supervision of Dr. Xianghua Xie. Robert obtained his BSc in Physics (Aber) and MSc in Medical Physics (Swansea).
Welcome to Dr. Rhodri Bevan who joined the group as a post-doc Research Assistant under the supervision of Dr. Xainghua Xie. Rhodri’s expertise is in computational modelling and he will be working on coronary disease modelling. This project is funded by the Welsh Office of Research and Development.