Outputs (11)

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.

IRIDiuM: immersive rendered interactive deep media (2016)
Presentation / Conference Contribution
Koniaris, B., Israr, A., Mitchell, K., Huerta, I., Kosek, M., Darragh, K., …Moon, B. (2016). IRIDiuM: immersive rendered interactive deep media. . https://doi.org/10.1145/2929490.2929496

Compelling virtual reality experiences require high quality imagery as well as head motion with six degrees of freedom. Most existing systems limit the motion of the viewer (prerecorded fixed position 360 video panoramas), or are limited in realism,... Read More about IRIDiuM: immersive rendered interactive deep media.

Stereohaptics: a haptic interaction toolkit for tangible virtual experiences (2016)
Presentation / Conference Contribution
Israr, A., Zhao, S., McIntosh, K., Schwemler, Z., Fritz, A., Mars, J., …Mitchell, K. (2016). Stereohaptics: a haptic interaction toolkit for tangible virtual experiences. In SIGGRAPH '16: ACM SIGGRAPH 2016 Studio. https://doi.org/10.1145/2929484.297027

With a recent rise in the availability of affordable head mounted gear sets, various sensory stimulations (e.g., visual, auditory and haptics) are integrated to provide seamlessly embodied virtual experience in areas such as education, entertainment,... Read More about Stereohaptics: a haptic interaction toolkit for tangible virtual experiences.

User, metric, and computational evaluation of foveated rendering methods (2016)
Presentation / Conference Contribution
Swafford, N. T., Iglesias-Guitian, J. A., Koniaris, C., Moon, B., Cosker, D., & Mitchell, K. (2016). User, metric, and computational evaluation of foveated rendering methods. In SAP '16 Proceedings of the ACM Symposium on Applied Perception. https://doi.

Perceptually lossless foveated rendering methods exploit human perception by selectively rendering at different quality levels based on eye gaze (at a lower computational cost) while still maintaining the user's perception of a full quality render. W... Read More about User, metric, and computational evaluation of foveated rendering methods.

Adaptive polynomial rendering (2016)
Presentation / Conference Contribution
Moon, B., McDonagh, S., Mitchell, K., & Gross, M. 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.