Outputs (76)

Real-time rendering with compressed animated light fields. (2017)
Presentation / Conference Contribution
Koniaris, B., Kosek, M., Sinclair, D., & Mitchell, K. (2017, May). Real-time rendering with compressed animated light fields. Presented at 43rd Graphics Interface Conference

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. By transforming offline rendered movie content into a novel immersive repr... Read More about Real-time rendering with compressed animated light fields..

Noise Reduction on G-Buffers for Monte Carlo Filtering: Noise Reduction on G-Buffers for Monte Carlo Filtering (2017)
Journal Article
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.13

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 and depth images. Our pre-filtering uses world positions and their variances... Read More about Noise Reduction on G-Buffers for Monte Carlo Filtering: Noise Reduction on G-Buffers for Monte Carlo Filtering.

Real-Time Multi-View Facial Capture with Synthetic Training (2017)
Journal Article
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 capture in real-time from multi-view helmet camera data, employing an actor sp... Read More about Real-Time Multi-View Facial Capture with Synthetic Training.

Rapid one-shot acquisition of dynamic VR avatars (2017)
Presentation / Conference Contribution
Malleson, C., Kosek, M., Klaudiny, M., Huerta, I., Bazin, J., Sorkine-Hornung, A., Mine, M., & Mitchell, K. (2017, March). Rapid one-shot acquisition of dynamic VR avatars. Presented at 2017 IEEE Virtual Reality (VR), Los Angeles, US

We present a system for rapid acquisition of bespoke, animatable, full-body avatars including face texture and shape. A blendshape rig with a skeleton is used as a template for customization. Identity blendshapes are used to customize the body and fa... Read More about Rapid one-shot acquisition of dynamic VR avatars.

Interactive Ray-Traced Area Lighting with Adaptive Polynomial Filtering (2016)
Presentation / Conference Contribution
Iglesias-Guitian, J. A., Moon, B., & Mitchell, K. (2016). Interactive Ray-Traced Area Lighting with Adaptive Polynomial Filtering. In Proceedings of the 13th European Conference on Visual Media Production (CVMP 2016)

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.

Synthetic Prior Design for Real-Time Face Tracking (2016)
Presentation / Conference Contribution
McDonagh, S., Klaudiny, M., Bradley, D., Beeler, T., Matthews, I., & Mitchell, K. (2016). Synthetic Prior Design for Real-Time Face Tracking. In 2016 Fourth International Conference on 3D Vision (3DV),. https://doi.org/10.1109/3dv.2016.72

Real-time facial performance capture has recently been gaining popularity in virtual film production, driven by advances in machine learning, which allows for fast inference of facial geometry from video streams. These learning-based approaches are s... Read More about Synthetic Prior Design for Real-Time Face Tracking.

Real-time Physics-based Motion Capture with Sparse Sensors (2016)
Presentation / Conference Contribution
Andrews, S., Huerta, I., Komura, T., Sigal, L., & Mitchell, K. (2016, December). Real-time Physics-based Motion Capture with Sparse Sensors. Presented at 13th European Conference on Visual Media Production (CVMP 2016) - CVMP 2016

We propose a framework for real-time tracking of humans using sparse multi-modal sensor sets, including data obtained from optical markers and inertial measurement units. A small number of sensors leaves the performer unencumbered by not requiring de... Read More about Real-time Physics-based Motion Capture with Sparse Sensors.

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..

Integrating real-time fluid simulation with a voxel engine (2016)
Journal Article
Zadick, J., Kenwright, B., & Mitchell, K. (2016). Integrating real-time fluid simulation with a voxel engine. The Computer Games Journal, 5(1-2), 55-64. https://doi.org/10.1007/s40869-016-0020-5

We present a method of adding sophisticated physical simulations to voxel-based games such as the hugely popular Minecraft (2012. http://minecraft.gamepedia.com/Liquid), thus providing a dynamic and realistic fluid simulation in a voxel environment.... Read More about Integrating real-time fluid simulation with a voxel engine.

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://d

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.