PG2013short

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https://diglib.eg.org/handle/10.2312/998

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Browsing PG2013short by Subject "Computational Geometry and Object Modeling"

Now showing 1 - 5 of 5
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    Bezier Crust on Quad Subdivision Surface
    (The Eurographics Association, 2013) Wang, Jianzhong; Cheng, Fuhua; Bruno Levy and Xin Tong and KangKang Yin
    Subdivision surfaces have been widely used in computer graphics and can be classified into two categories, approximating and interpolatory. Representative approximating schemes are Catmull-Clark (quad) and Loop (triangular). Although widely used, one issue remains with the approximating schemes, i.e., the process of interpolating a set of data points is a global process so it is difficult to interpolate large data sets. In this paper, we present a local interpolation scheme for quad subdivision surfaces through appending a G2 Bezier crust to the underlying surface, and show that this local interpolation scheme does not change the curvatures across the boundaries of underlying subdivision patches, therefore, one obtains high quality interpolating limit surfaces for engineering and graphics applications efficiently.
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    Fast Random Sampling of Triangular Meshes
    (The Eurographics Association, 2013) Sik, Martin; Krivanek, Jaroslav; Bruno Levy and Xin Tong and KangKang Yin
    We present a simple and fast algorithm for generating randomly distributed points on a triangle mesh with probability density specified by a two-dimensional texture. Efficiency is achieved by resampling the density texture on an adaptively subdivided version of the input mesh. This allows us to generate the samples up to 40 x faster than the rejection sampling algorithm, the fastest existing alternative. We demonstrate the algorithm in two applications: fast placement of hair roots on a surface and sampling of illumination from a complex luminaire. Part of our mesh sampling procedure is a new general acceleration technique for drawing samples from a 1D discrete probability distribution whose utility extends beyond the mesh sampling problem.
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    An Improved Friction Model for Cloth Simulation
    (The Eurographics Association, 2013) Wong, Tszho H.; Leach, Geoff; Zambetta, Fabio; Bruno Levy and Xin Tong and KangKang Yin
    Friction is a complex phenomenon that resists tangential motion between two contacting objects. In computer graphics, existing cloth simulation methods have typically used a Coulomb model for friction, both static and kinetic. However, the Coulomb model is limited since it intends to capture fundamental frictional phenomena. Many observed friction effects such as stiction, Stribeck friction, viscous friction and the stick-slip phenomenon are not modelled by it. This paper describes an improved physically based friction model for simulating such effects, extending the Coulomb model.We show that including these additional effects is relatively straightforward. Results and comparisons with a pure Coulomb model are provided to demonstrate the capability and features of the improved model.
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    Intelligent Interactive Volume Classification
    (The Eurographics Association, 2013) Grau, Sergi; Puig, Anna; Escalera, Sergio; Salamó, Maria; Bruno Levy and Xin Tong and KangKang Yin
    This paper defines an intelligent and interactive framework to classify multiple regions of interest from the original data on demand, without requiring any preprocessing or previous segmentation. The proposed intelligent and interactive approach is divided in three stages: visualize, training and testing. First, users visualize and label some samples directly on slices of the volume. Training and testing are based on a framework of Error Correcting Output Codes and Adaboost classifiers that learn to classify each region the user has painted. Later, at the testing stage, each classifier is directly applied on the rest of samples and combined to perform multi-class labeling, being used in the final rendering. We also parallelized the training stage using a GPU-based implementation for obtaining a rapid interaction and classification.
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    Non-rigid 3D Shape Retrieval via Sparse Representation
    (The Eurographics Association, 2013) Wan, Lili; Li, Shuai; Miao, Zhenjiang J.; Cen, Yigang G.; Bruno Levy and Xin Tong and KangKang Yin
    Shape descriptor design is an important but challenging problem for non-rigid 3D shape retrieval. Recently, bagof- words based methods are widely used to integrate a model's local shape descriptors into a global histogram. In this paper, we present a new method to pool the local shape descriptors into a global shape descriptor by means of sparse representation. Firstly, we employ heat kernel signature (HKS) to depict the multi-scale local shape. Then, for each model in the training dataset, we take the HKSs corresponding to its mesh vertices to serve as training signals, and thus an over-complete dictionary can be learned from them. Finally, the HKSs of each 3D model are sparsely coded based on the learned dictionary, and such sparse representations can be further integrated to form an object-level shape descriptor. Moreover, we conduct extensive experiments on the state-of-the-art benchmarks, wherein comprehensive evaluations state our method can achieve better performance than other bag-of-words based approaches.