S t e r e o c o n t e n t D i s t o r t e d d i s p a r i t y D i s p a r i t y Q u a n z e N o i s e C o mp r e s s Figure 1: A metric derived from our model, that predicts the perceived difference (right) between original and distorted disparity (middle). AbstractBinocular disparity is an important cue for the human visual system to recognize spatial layout, both in reality and simulated virtual worlds. This paper introduces a perceptual model of disparity for computer graphics that is used to define a metric to compare a stereo image to an alternative stereo image and to estimate the magnitude of the perceived disparity change. Our model can be used to assess the effect of disparity to control the level of undesirable distortions or enhancements (introduced on purpose). A number of psycho-visual experiments are conducted to quantify the mutual effect of disparity magnitude and frequency to derive the model. Besides difference prediction, other applications include compression, and re-targeting. We also present novel applications in form of hybrid stereo images and backward-compatible stereo. The latter minimizes disparity in order to convey a stereo impression if special equipment is used but produces images that appear almost ordinary to the naked eye. The validity of our model and difference metric is again confirmed in a study.
Conservative Rasterization Conservative voxelization Voxelization via rasterization (from 3 directions) Octree-based sparse solid voxelizationFigure 1: Our methods can rapidly create surface and solid voxelizations, surpassing the limitations of rasterization-based approaches. Left: The conservative voxelization robustly captures all overlapped voxels. Right: Exploiting the uniformity of large voxel regions, we can directly perform solid voxelization into a sparse octree, significantly reducing the memory requirements. AbstractThis paper presents data-parallel algorithms for surface and solid voxelization on graphics hardware. First, a novel conservative surface voxelization technique, setting all voxels overlapped by a mesh's triangles, is introduced, which is up to one order of magnitude faster than previous solutions leveraging the standard rasterization pipeline. We then show how the involved new triangle/box overlap test can be adapted to yield a 6-separating surface voxelization, which is thinner but still connected and gap-free. Complementing these algorithms, both a triangle-parallel and a tile-based technique for solid voxelization are subsequently presented. Finally, addressing the high memory consumption of high-resolution voxel grids, we introduce a novel octree-based sparse solid voxelization approach, where only close to the solid's boundary finestlevel voxels are stored, whereas uniform interior and exterior regions are represented by coarser-level voxels. This representation is created directly from a mesh without requiring a full intermediate solid voxelization, enabling GPU-based voxelizations of unprecedented size.
We present a new shape representation, the multi-level partition of unity implicit surface, that allows us to construct surface models from very large sets of points. There are three key ingredients to our approach: 1) piecewise quadratic functions that capture the local shape of the surface, 2) weighting functions (the partitions of unity) that blend together these local shape functions, and 3) an octree subdivision method that adapts to variations in the complexity of the local shape. Our approach gives us considerable flexibility in the choice of local shape functions, and in particular we can accurately represent sharp features such as edges and corners by selecting appropriate shape functions. An error-controlled subdivision leads to an adaptive approximation whose time and memory consumption depends on the required accuracy. Due to the separation of local approximation and local blending, the representation is not global and can be created and evaluated rapidly. Because our surfaces are described using implicit functions, operations such as shape blending, offsets, deformations and CSG are simple to perform
Figure 1: Complex lens flare generated by a Canon zoom lens. Left: reference photos. Right: renderings generated using our technique at comparable settings. Even with many unknowns in the lens design and scene composition, as well as manufacturing tolerances in the real lens, the renderings closely reproduce the "personality" of the flare. AbstractLens flare is caused by light passing through a photographic lens system in an unintended way. Often considered a degrading artifact, it has become a crucial component for realistic imagery and an artistic means that can even lead to an increased perceived brightness. So far, only costly offline processes allowed for convincing simulations of the complex light interactions. In this paper, we present a novel method to interactively compute physically-plausible flare renderings for photographic lenses. The underlying model covers many components that are important for realism, such as imperfections, chromatic and geometric lens aberrations, and antireflective lens coatings. Various acceleration strategies allow for a performance/quality tradeoff, making our technique applicable both in real-time applications and in high-quality production rendering. We further outline artistic extensions to our system.
Figure 1: Stages of light source measurement and rendering (from left to right): a) photo of flashlight -b) flashlight in measurement setupc) 2D reconstruction of the measured data in a virtual plane -d) measured light used in a global illumination simulation. AbstractRealistic image synthesis requires both complex and realistic models of real-world light sources and efficient rendering algorithms to deal with them. In this paper, we describe a processing pipeline for dealing with complex light sources from acquisition to global illumination rendering. We carefully design optical filters to guarantee high precision measurements of real-world light sources. We discuss two practically feasible setups that allow us to measure light sources with different characteristics. Finally, we introduce an efficient importance sampling algorithm for our representation that can be used, for example, in conjunction with Photon Maps.
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