Rendering - Experimental Ideas & Implementations 2015

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https://diglib.eg.org/handle/10.2312/12636

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Browsing Rendering - Experimental Ideas & Implementations 2015 by Subject "I.3.6 [Computer Graphics]"

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    Efficient Visibility Heuristics for kd-trees Using the RTSAH
    (The Eurographics Association, 2015) Moulin, Matthias; Billen, Niels; Dutré, Philip; Jaakko Lehtinen and Derek Nowrouzezahrai
    Acceleration data structures such as kd-trees aim at reducing the per-ray cost which is crucial for rendering performance. The de-facto standard for constructing kd-trees, the Surface Area Heuristic (SAH), does not take ray termination into account and instead assumes rays never hit a geometric primitive. The Ray Termination Surface Area Heuristic (RTSAH) is a cost metric originally used for determining the traversal order of the voxels for occlusion rays that takes ray termination into account. We adapt this RTSAH to building kd-trees that aim at reducing the per-ray cost of rays. Our build procedure has the same overall computational complexity and considers the same finite set of splitting planes as the SAH. By taking ray termination into account, we favor cutting off child voxels which are not or hardly visible to each other. This results in fundamentally different and more qualitative kd-trees compared to the SAH.
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    GPU-based Out-of-Core HLBVH Construction
    (The Eurographics Association, 2015) Zeidan, Mahmoud; Nazmy, Taymoor; Aref, Mostafa; Jaakko Lehtinen and Derek Nowrouzezahrai
    Recently the GPU has been used extensively in building indexing structures for moderately complex scenes that fit inside the GPU core. However, only few methods have been developed for constructing indexing structures for massive models larger than GPU memory. In this paper, we present an out-of-core HLBVH algorithm, a new method for constructing spatial hierarchies suitable for massive models that cannot fit into GPU device memory. A key insight of our method is how to bring and process out-of-core data blocks that do not fit into available device memory. Results show that our approach can compete with HLBVH hierarchy builder for large models on CPU. We also demonstrate the value of our algorithms in a GPU-based out-of-core path tracer that brings tree nodes and geometry into GPU core as needed, and efficiently achieve complex global illumination effects for models up to hundred million triangles.