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    Path-Traced Motion Blur using Motion Trees

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    Date
    2020
    Author
    Martinek, Magdalena
    Thiemann, Philip
    Stamminger, Marc
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    Abstract
    Motion Blur is an important effect of photo-realistic rendering. Distribution ray tracing can simulate motion blur very well by integrating light, both over the spatial and the temporal domain. However, increasing the problem by the temporal dimension entails many challenges, particularly in cinematic multi-bounce path tracing of complex scenes where heavy-weight geometry with complex lighting and even offscreen elements contribute to the final image. In particular, for fast moving objects, undersampling in the time domain results in severe artefacts. In this paper, we propose the Motion Tree, a novel Level-of-Detail data structure for efficient handling of animated objects, that both filters in the spatial and the temporal domain. The Motion Tree is a compact nesting of a temporal interval binary tree for filtering time consecutive data and a sparse voxel octree (SVO) which simplifies spatially nearby data. It is generated during a pre-process and fits nicely into any conventional physically based path tracer. When used in a production-scale environment it significantly reduces memory requirements allowing for a speedup in rendering performance with user control over the degree of impact on quality.
    BibTeX
    @inproceedings {ag.20201251,
    booktitle = {Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference},
    editor = {Biasotti, Silvia and Pintus, Ruggero and Berretti, Stefano},
    title = {{Path-Traced Motion Blur using Motion Trees}},
    author = {Martinek, Magdalena and Thiemann, Philip and Stamminger, Marc},
    year = {2020},
    publisher = {The Eurographics Association},
    ISSN = {2617-4855},
    ISBN = {978-3-03868-124-3},
    DOI = {10.2312/stag.20201251}
    }
    URI
    https://doi.org/10.2312/stag.20201251
    https://diglib.eg.org:443/handle/10.2312/stag20201251
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    Eurographics Association copyright © 2013 - 2020 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA