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Senior Research Fellow
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Li, Y., Wiedemann, P., & Mitchell, K. (2019). Deep Precomputed Radiance Transfer for Deformable Objects. Proceedings of the ACM on Computer Graphics and Interactive Techniques, 2(1), 1-16. https://doi.org/10.1145/3320284
We propose, DeepPRT, a deep convolutional neural network to compactly encapsulate the radiance transfer of a freely deformable object for rasterization in real-time.
Casas, L., Fauconneau, M., Kosek, M., Mclister, K., & Mitchell, K. (2019). Enhanced Shadow Retargeting with Light-Source Estimation Using Flat Fresnel Lenses. Computers, 8(2), https://doi.org/10.3390/computers8020029
Shadow-retargeting maps depict the appearance of real shadows to virtual shadows given corresponding deformation of scene geometry, such that appearance is seamlessly maintain...
Koniaris, B., Kosek, M., Sinclair, D., & Mitchell, K. (2018). GPU-accelerated depth codec for real-time, high-quality light field reconstruction. Proceedings of the ACM on Computer Graphics and Interactive Techniques, 1(1), 1-15. doi:10.1145/3203193
Pre-calculated depth information is essential for efficient light field video rendering, due to the prohibitive cost of depth estimation from color when real-time performance ...
Scottish Funding Council
The solution for the synchronisation issue was to include a simultaneous animation of the journey and the weather data. This provided an intuitive visualisation of two independent sets of data.
The DISTRO network brings together leading laboratories in Visual Computing and 3D Computer Graphics research across Europe with the aim of training a new generation of scientists, technologists, and ...
Calian, D. A., Lalonde, J., Gotardo, P., Simon, T., Matthews, I., & Mitchell, K. (2018). From Faces to Outdoor Light Probes. Computer Graphics Forum, 37(2), 51-61. doi:10.1111/cgf.13341
Image‐based lighting has allowed the creation of photo‐realistic computer‐generated content. However, it requires the accurate capture of the illumination conditions, a task n...
Pan, Y., Sinclair, D., & Mitchell, K. (2018). Empowerment and embodiment for collaborative mixed reality systems: Empowerment and Embodiment. Computer Animation and Virtual Worlds, 29(3-4), e1838. https://doi.org/10.1002/cav.1838
We present several mixed‐reality‐based remote collaboration settings by using consumer head‐mounted displays. We investigated how two people are able to work together in these...
Koniaris, C., Kosek, M., Sinclair, D., & Mitchell, K. (2019). Compressed Animated Light Fields with Real-time View-dependent Reconstruction. IEEE Transactions on Visualization and Computer Graphics, 25(4), 1666-1680. https://doi.org/10.1109/tvcg.2018.2818156
We propose an end-to-end solution for presenting movie quality animated graphics to the user while still allowing the sense of presence afforded by free viewpoint head motion....
Klaudiny, M., McDonagh, S., Bradley, D., Beeler, T., & Mitchell, K. (2017). Real-Time Multi-View Facial Capture with Synthetic Training. Computer Graphics Forum, 36(2), 325-336. https://doi.org/10.1111/cgf.13129
We present a real-time multi-view facial capture system facilitated by synthetic training imagery. Our method is able to achieve high-quality markerless facial performance cap...
Moon, B., Iglesias-Guitian, J. A., McDonagh, S., & Mitchell, K. (2017). Noise Reduction on G-Buffers for Monte Carlo Filtering: Noise Reduction on G-Buffers for Monte Carlo Filtering. Computer Graphics Forum, 36(8), 600-612. https://doi.org/10.1111/cgf.13155
We propose a novel pre-filtering method that reduces the noise introduced by depth-of-field and motion blur effects in geometric
buffers (G-buffers) such as texture, normal an...
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 n...
Bitterli, B., Rousselle, F., Moon, B., Iglesias-Guitián, J. A., Adler, D., Mitchell, K., …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 ran...
Moon, B., McDonagh, S., Mitchell, K., & Gross, M. (2016). Adaptive polynomial rendering. ACM transactions on graphics, 35(4), 1-10. https://doi.org/10.1145/2897824.2925936
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 preservin...
Bradbury, G. A., Subr, K., Koniaris, C., Mitchell, K., & Weyrich, T. (2015). Guided ecological simulation for artistic editing of plant distributions in natural scenes. The Journal of Computer Graphics Techniques, 4(4),
In this paper we present a novel approach to author vegetation cover of large natural scenes. Unlike stochastic scatter-instancing tools for plant placement (such as multi-cla...
Moon, B., Iglesias-Guitian, J. A., Yoon, S., & Mitchell, K. (2015). Adaptive rendering with linear predictions. ACM transactions on graphics, 34(4), 121:1-121:11. https://doi.org/10.1145/2766992
We propose a new adaptive rendering algorithm that enhances the
performance of Monte Carlo ray tracing by reducing the noise, i.e.,
variance, while preserving a variety of hig...
Subr, K., Nowrouzezahrai, D., Jarosz, W., Kautz, J., & Mitchell, K. (2014). Error analysis of estimators that use combinations of stochastic sampling strategies for direct illumination. Computer Graphics Forum, 33(4), 93-102. https://doi.org/10.1111/cgf.12416
We present a theoretical analysis of error of combinations of Monte Carlo estimators used in image synthesis. Importance sampling and multiple importance sampling are popular ...
Chen, A., Chen, Z., Zhang, G., Zhang, Z., Mitchell, K., & Yu, J. Photo-Realistic Facial Details Synthesis from Single Image. In IEEE International Conference on Computer Vision (ICCV), (9429-9439)
We present a single-image 3D face synthesis technique that can handle challenging facial expressions while recovering fine geometric details. Our technique employs expression ...
This research will investigate the nature of interactions between people and experience-oriented technologies such as new-media artw...
Autism Spectrum Disorder (ASD) is a lifelong neurodevelopmental disorder that can affect people in a number...
Augmented Reality (AR) aims to extend the physical world through virtual content. To perform such addition in an unnoticeable way, a variety of technical constraints need to be su...
CoRe44, room C44, Merchiston Campus
25 September 2018