Interactive Ray-Traced Area Lighting with Adaptive Polynomial Filtering (2016)
Presentation / Conference Contribution
Iglesias-Guitian, J. A., Moon, B., & Mitchell, K. (2016, December). Interactive Ray-Traced Area Lighting with Adaptive Polynomial Filtering. Presented at CVMP, The 13th European Conference on Visual Media Production, London, UK

Area lighting computation is a key component for synthesizing photo-realistic rendered images, and it simulates plausible soft shadows by considering geometric relationships between area lights and three-dimensional scenes, in some cases even account... Read More about Interactive Ray-Traced Area Lighting with Adaptive Polynomial Filtering.

Pixel history linear models for real-time temporal filtering. (2016)
Journal Article
Iglesias-Guitian, J. A., Moon, B., Koniaris, C., Smolikowski, E., & Mitchell, K. (2016). Pixel history linear models for real-time temporal filtering. Computer Graphics Forum, 35(7), 363-372. https://doi.org/10.1111/cgf.13033

We propose a new real-time temporal filtering and antialiasing (AA) method for rasterization graphics pipelines. Our method is based on Pixel History Linear Models (PHLM), a new concept for modeling the history of pixel shading values over time using... Read More about Pixel history linear models for real-time temporal filtering..

MLCut: exploring multi-level cuts in dendrograms for biological data (2016)
Presentation / Conference Contribution
Vogogias, A., Kennedy, J., Archambault, D., Anne Smith, V., & Currant, H. (2016, September). MLCut: exploring multi-level cuts in dendrograms for biological data. Presented at Computer Graphics & Visual Computing (CGVC) 2016

Choosing a single similarity threshold for cutting dendrograms is not sufficient for performing hierarchical clustering analysis of heterogeneous data sets. In addition, alternative automated or semi-automated methods that cut dendrograms in multiple... Read More about MLCut: exploring multi-level cuts in dendrograms for biological data.

Nonlinearly Weighted First-order Regression for Denoising Monte Carlo Renderings (2016)
Journal Article
Bitterli, B., Rousselle, F., Moon, B., Iglesias-Guitián, J. A., Adler, D., Mitchell, K., Jarosz, W., & Novák, J. (2016). Nonlinearly Weighted First-order Regression for Denoising Monte Carlo Renderings. Computer Graphics Forum, 35(4), 107-117. https://doi.org/10.1111/cgf.12954

We address the problem of denoising Monte Carlo renderings by studying existing approaches and proposing a new algorithm that yields state-of-the-art performance on a wide range of scenes. We analyze existing approaches from a theoretical and empiric... Read More about Nonlinearly Weighted First-order Regression for Denoising Monte Carlo Renderings.

Adaptive polynomial rendering (2016)
Presentation / Conference Contribution
Moon, B., McDonagh, S., Mitchell, K., & Gross, M. (2016, July). Adaptive polynomial rendering. Presented at ACM SIGGRAPH 2016, Anaheim, California, US

In this paper, we propose a new adaptive rendering method to improve the performance of Monte Carlo ray tracing, by reducing noise contained in rendered images while preserving high-frequency edges. Our method locally approximates an image with polyn... Read More about Adaptive polynomial rendering.

The Ensoulment of Virtual Space Minecraft as a Tool for Engaging With a Sculpture Park (2016)
Presentation / Conference Contribution
Flint, T., Turner, P., & Banach, A. (2016, June). The Ensoulment of Virtual Space Minecraft as a Tool for Engaging With a Sculpture Park. Presented at 15th International Conference on Interaction Design and Children - IDC '16

This is a demonstration of a Minecraft facsimile of Jupiter Artland, a sculpture park on the outskirts of Edinburgh. With the cooperation of primary school children we developed a mixed reality game employing Minecraft. Our aim is to investigate atta... Read More about The Ensoulment of Virtual Space Minecraft as a Tool for Engaging With a Sculpture Park.

Hierarchical Clustering with Multiple-Height Branch-Cut Applied to Short Time-Series Gene Expression Data (2016)
Presentation / Conference Contribution
Vogogias, A., Kennedy, J., & Archambault, D. (2016, July). Hierarchical Clustering with Multiple-Height Branch-Cut Applied to Short Time-Series Gene Expression Data. Presented at Eurovis 2016

Rigid adherence to pre-specified thresholds and static graphical representations can lead to incorrect decisions on merging of clusters. As an alternative to existing automated or semi-automated methods, we developed a visual analytics approach for p... Read More about Hierarchical Clustering with Multiple-Height Branch-Cut Applied to Short Time-Series Gene Expression Data.