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Now showing 1 - 3 of 3
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    Bidirectional Clustering for Scalable VPL-based Global Illumination
    (The Eurographics Association, 2015) Jarabo, Adrian; Buisan, Raul; Gutierrez, Diego; Mateu Sbert and Jorge Lopez-Moreno
    Virtual Point Lights (VPL) methods approximate global illumination (GI) in a scene by using a large number of virtual lights modeling the reflected radiance of a surface. These methods are efficient, and allow computing noise-free images significantly faster that other methods. However, they scale linearly with the number of virtual lights and with the number of pixels to be rendered. Previous approaches improve the scalability of the method by hierarchically evaluating the virtual lights, allowing sublinear performance with respect the lights being evaluated. In this work, we introduce a novel bidirectional clustering approach, by hierarchically evaluating both the virtual lights and the shading points. This allows reusing radiance evaluation between pixels, and obtaining sublinear costs with respect to both lights and camera samples. We demonstrate significantly better performance than state-of-the-art VPL clustering methods with several examples, including high-resolution images, distributed effects, and rendering of light fields.
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    Low Cost Decomposition of Direct and Global Illumination in Real Scenes
    (The Eurographics Association, 2015) Garces, Elena; Martin, Fernando; Gutierrez, Diego; Mateu Sbert and Jorge Lopez-Moreno
    Recent advances in the field of computational light transport have made it possible to solve previously unsolvable problems thanks to incorporating new devices and techniques. One of these problems is the decomposition of the illumination into its local and global components in real scenes. Previous work has managed to perform such a decomposition by projecting several light patterns on a target scene and processing its captures. In this work we build on that approach and propose two novel contributions: first, a new interpolation method, which allows the decomposition of the light components from a single capture of the projected scene into the native resolution, without requiring down-sampling; second, we propose an implementation of the algorithm for a mobile platform.
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    Compressive High Speed Video Acquisition
    (The Eurographics Association, 2015) Serrano, Ana; Gutierrez, Diego; Masia, Belen; Mateu Sbert and Jorge Lopez-Moreno
    Traditional video capture is limited by the trade-off between spatial and temporal resolution. When capturing videos of high temporal resolution, the spatial resolutions decreases due to bandwidth limitations in the capture system. Achieving both high spatial and temporal resolution is only possible with highly specialized and very expensive hardware; although the bandwidth is higher, the same basic trade-off remains. In this paper, we make use of a single-shot, high-speed video capture system, in order to overcome this limitation. It is based on compressive sensing, and relies on dictionary learning for sparse video representation. This allows capturing a video sequence by coding the temporal information in a single frame, and then reconstructing the full video sequence from this single coded image. We perform an in-depth analysis of the parameters of influence in the system, providing insights for future developments of similar systems.