Browsing by Author "Lin, Daqi"

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    Hardware Adaptive High-Order Interpolation for Real-Time Graphics
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Lin, Daqi; Seiler, Larry; Yuksel, Cem; Binder, Nikolaus and Ritschel, Tobias
    Interpolation is a core operation that has widespread use in computer graphics. Though higher-order interpolation provides better quality, linear interpolation is often preferred due to its simplicity, performance, and hardware support. We present a unified refactoring of quadratic and cubic interpolations as standard linear interpolation plus linear interpolations of higher-order terms and show how they can be applied to regular grids and (triangular/tetrahedral) simplexes Our formulations can provide significant reduction in computation cost, as compared to typical higher-order interpolations and prior approaches that utilize existing hardware linear interpolation support to achieve higher-order interpolation. In addition, our formulation allows approximating the results by dynamically skipping some higher order terms with low weights for further savings in both computation and storage. Thus, higher-order interpolation can be performed adaptively, as needed. We also describe how relatively minor modifications to existing GPU hardware could provide hardware support for quadratic and cubic interpolations using our approach for both texture filtering operations and barycentric interpolation. We present a variety of examples using triangular, rectangular, tetrahedral, and cuboidal interpolations, showing the effectiveness of our higher-order interpolations in different applications.
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    Virtual Blue Noise Lighting
    (ACM Association for Computing Machinery, 2022) Li, Tianyu; Wang, Wenyou; Lin, Daqi; Yuksel, Cem; Josef Spjut; Marc Stamminger; Victor Zordan
    We introduce virtual blue noise lighting, a rendering pipeline for estimating indirect illumination with a blue noise distribution of virtual lights. Our pipeline is designed for virtual lights with non-uniform emission profiles that are more expensive to store, but required for properly and efficiently handling specular transport. Unlike the typical virtual light placement approaches that traverse light paths from the original light sources, we generate them starting from the camera. This avoids two important problems: wasted memory and computation with fully-occluded virtual lights, and excessive virtual light density around high-probability light paths. In addition, we introduce a parallel and adaptive sample elimination strategy to achieve a blue noise distribution of virtual lights with varying density. This addresses the third problem of virtual light placement by ensuring that they are not placed too close to each other, providing better coverage of the (indirectly) visible surfaces and further improving the quality of the final lighting estimation. For computing the virtual light emission profiles, we present a photon splitting technique that allows efficiently using a large number of photons, as it does not require storing them. During lighting estimation, our method allows using both global power-based and local BSDF important sampling techniques, combined via multiple importance sampling. In addition, we present an adaptive path extension method that avoids sampling nearby virtual lights for reducing the estimation error. We show that our method significantly outperforms path tracing and prior work in virtual lights in terms of both performance and image quality, producing a fast but biased estimate of global illumination.