Path-space Motion Estimation and Decomposition for Robust Animation Filtering

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dc.contributor.authorZimmer, Henningen_US
dc.contributor.authorRousselle, Fabriceen_US
dc.contributor.authorJakob, Wenzelen_US
dc.contributor.authorWang, Oliveren_US
dc.contributor.authorAdler, Daviden_US
dc.contributor.authorJarosz, Wojciechen_US
dc.contributor.authorSorkine-Hornung, Olgaen_US
dc.contributor.authorSorkine-Hornung, Alexanderen_US
dc.contributor.editorJaakko Lehtinen and Derek Nowrouzezahraien_US
dc.date.accessioned2015-06-23T04:49:08Z
dc.date.available2015-06-23T04:49:08Z
dc.date.issued2015en_US
dc.description.abstractRenderings of animation sequences with physics-based Monte Carlo light transport simulations are exceedingly costly to generate frame-by-frame, yet much of this computation is highly redundant due to the strong coherence in space, time and among samples. A promising approach pursued in prior work entails subsampling the sequence in space, time, and number of samples, followed by image-based spatio-temporal upsampling and denoising. These methods can provide significant performance gains, though major issues remain: firstly, in a multiple scattering simulation, the final pixel color is the composite of many different light transport phenomena, and this conflicting information causes artifacts in image-based methods. Secondly, motion vectors are needed to establish correspondence between the pixels in different frames, but it is unclear how to obtain them for most kinds of light paths (e.g. an object seen through a curved glass panel). To reduce these ambiguities, we propose a general decomposition framework, where the final pixel color is separated into components corresponding to disjoint subsets of the space of light paths. Each component is accompanied by motion vectors and other auxiliary features such as reflectance and surface normals. The motion vectors of specular paths are computed using a temporal extension of manifold exploration and the remaining components use a specialized variant of optical flow. Our experiments show that this decomposition leads to significant improvements in three image-based applications: denoising, spatial upsampling, and temporal interpolation.en_US
dc.description.number4en_US
dc.description.sectionheadersReal-time Rendering and Filteringen_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume34en_US
dc.identifier.doi10.1111/cgf.12685en_US
dc.identifier.pages131-142en_US
dc.identifier.urihttps://doi.org/10.1111/cgf.12685en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectI.3.7 [Computer Graphics]en_US
dc.subjectThree Dimensional Graphics and Realismen_US
dc.subjectI.3.7 [Computer Graphics]en_US
dc.subjectColoren_US
dc.subjectshadingen_US
dc.subjectshadowingen_US
dc.subjectand textureen_US
dc.titlePath-space Motion Estimation and Decomposition for Robust Animation Filteringen_US
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34-Issue 4
EGSR15: 26th Eurographics Symposium on Rendering