PG2012short

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https://diglib.eg.org/handle/10.2312/997

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    Bokeh Rendering with a Physical Lens
    (The Eurographics Association, 2012) Liu, Xin; Rokne, Jon; Chris Bregler and Pedro Sander and Michael Wimmer
    Bokeh is important for the realism and aesthetics of graphical rendering, but hard to simulate. In this paper, we propose a novel method that conceptually shoots a 3D display with a physical camera. While a high-quality 3D display is not available, we render the 3D scene layer by layer on a 2D display, and shoot each rendered layer with a physical camera whose focus is adjusted to produce the right amount of blurs. The pure colours and opacities of each layer are extracted by a matting technique and then combined into a single image by alpha blending. The proposed method provides an alternative to bokeh simulation by purely computational algorithms.
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    Real-time Particle Fluid Simulation with WCSPH
    (The Eurographics Association, 2012) Zhang, Fengquan; Shen, Xukun; Long, Xiang; Zhao, Bin; Hu, Lei; Chris Bregler and Pedro Sander and Michael Wimmer
    In this paper, based on weakly compressible smoothed particles hydrodynamics (WCSPH), we present a method for simulating high quality fluid. We propose a new pressure equation to reduce time overhead, speed up convergence towards small density fluctuations and allow for a larger time step than that of traditional approaches. And based on the new equation, we introduce a new adaptive time-stepping approach that automatically adapts the time step according to each particle current individual time step, thus improving the efficiency of computation and contributing much to a real-time particle fluid simulation. For real-time simulation, we make full use of CPU and GPU in a combined way to build a parallel platform, namely Multi-GPU platform. And optimization of the platform design is made to run a simulation with realistic visual effects in real time.
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    Optimizing Geometry-aware Pants Decomposition
    (The Eurographics Association, 2012) Zhang, Kang; Li, Xin; Chris Bregler and Pedro Sander and Michael Wimmer
    We present a computational framework to optimize the pants decomposition of surfaces with non-trivial topology. A pants decomposition segments a surface into a set of sub-patches each of which is genus-0 with 3 boundaries. A given surface usually admits infinitely-many pants decompositions that are topologically inequivalent. Given some pre-determined geometric criteria, our algorithm enumerates different classes of pants decompositions and search for the optimal one. The proposed framework is general, and can be used to generate different suitable segmentations according to different applications. We also generalize our algorithm for consistent decomposition of multiple surfaces. This algorithm can be used in constructing compatible cross-surface mapping, and facilitate many computer graphics tasks.
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    User-Assisted Disparity Maps
    (The Eurographics Association, 2012) Chen, Hsin-Yi; Lin, Yi-Shan; Shen, I-Chao; Luo, Sheng-Jie; Cheng, Wen-Huang; Chen, Bing-Yu; Chris Bregler and Pedro Sander and Michael Wimmer
    In this paper, we present an intuitive and efficient system for correcting the artifacts and noises caused by imperfect disparity estimation. Disparity estimation is a very important and basic process for almost all stereoscopic 3D applications. Although there are many disparity estimation methods, none of them are perfect and suitable for any arbitrary case. Given a defect disparity map estimated from a stereoscopic image pair, our system incorporates some simple user hints and rich information derived from sparse feature matching as guides for disparity correction. We also utilize 3D connectivity prior and planarity assumption to overcome the challenge presented by textureless surfaces and occluded regions. By providing an intuitive user interface with integrated stereo visualization, our system allows novel users to correct their own disparity maps easily.
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    Point-wise Adaptive Filtering for Fast Monte Carlo Noise Reduction
    (The Eurographics Association, 2012) Guo, Jie; Pan, Jingui; Chris Bregler and Pedro Sander and Michael Wimmer
    Monte Carlo based photorealistic image synthesis has proven to be one of the most flexible and powerful rendering techniques, but is plagued with undesirable artifacts known as Monte Carlo noise. We present an adaptive filtering method designed for Monte Carlo rendering systems that counteracts noise while respecting sharp features. The filter operates as a post-process on a noisy image augmented with three screen-space geometric attribute buffers, and by using a point-wise adaptive (varying window size) filtering kernel, this method is able to reinforce the preservation of important scene reflected edges, in less time. Comparative results demonstrate the simplicity and efficiency of our method, which makes it a feasible and robust solution for smoothing noisy images generated by Monte Carlo rendering techniques. CUDA implementation also makes the algorithm potentially practical for interactive Monte Carlo rendering in the near future.
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    Ellipsoidal Cube Maps for Accurate Rendering of Planetary-Scale Terrain Data
    (The Eurographics Association, 2012) Lambers, Martin; Kolb, Andreas; Chris Bregler and Pedro Sander and Michael Wimmer
    Advances in sensor technology lead to a rapidly growing number of terrain data sets with very high spatial resolution. To allow reliable visual analysis of this data, terrain data for planetary objects needs to be rendered with accurate reproduction of every detail. This combination of very large scale and very fine detail is challenging for multiple reasons: the numerical accuracy of typical data types is not sufficient, simple spherical planet models fail to accurately represent the data, and distortions in map projections used for data storage lead to sampling problems. In this paper, we propose the Ellipsoidal Cube Map model to address these problems. We demonstrate the possibilities of the model using a simple renderer implementation that achieves interactive frame rates for a variety of data sets for Earth, Moon, and Mars.