PG2014short

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https://diglib.eg.org/handle/10.2312/7750

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Browsing PG2014short by Subject "Computational Geometry and Object Modeling"

Now showing 1 - 4 of 4
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    Automatic Garment Modeling From Front And Back Images
    (The Eurographics Association, 2014) Huang, Lifeng; Gao, Chengying; John Keyser and Young J. Kim and Peter Wonka
    We present a system which can automatically generate a realistic garment model from two images of an existing garment. Without the requirement of tailoring expertise and tedious operation, our method takes the front and back images of a real garment as input, and the system will make reasonable geometric modeling as well as physical simulation of the garment. Combining with mannequin's skeleton information, we propose a panel positioning method to place garment panels in appropriate positions. A key feature of our system is to automatically interpret sewn information, which effectively simplifies user interaction. In addition, panel deformation method based on mannequin's pose allows easy data capture. It extends the flexibility and utility of our method. The experiments demonstrate the effectiveness on generating models of various garment styles.
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    Incorporating Fiber Controls into FEM Model for Transversely Isotropic Materials
    (The Eurographics Association, 2014) Jianping, Cai; Feng, Lin; Tsui, Lee Yong; Kemao, Qian; Soon, Seah Hock; John Keyser and Young J. Kim and Peter Wonka
    Physically plausible deformable models based on continuum mechanics have been a hot topic in computer graphics for decades, and many models have been proposed to improve performance speed and stability. However, most of the existing models focus on isotropic materials, while elastic objects with complex anisotropic properties are less studied. Based on the observation that a large group of objects have specific internal structures (fibers) that determine their anisotropic behavior, we propose a fiber incorporated corotational FEM model that can approximate longitudinally anisotropic deformation. First, a fiber orientation field is used to establish local frames for each element; then, the orientation information is combined into the FEM model by adding local transformations on element stiffness matrices. This proposed model can provide a control for directable deformations, and yields realistic anisotropic deformations. Large deformations can be accommodated; meanwhile, with pre-computation it adds no computational cost to the existing corotational FEM model during simulation. Convincing experimental results and analytical comparisons are presented, together with an accompanying video demonstration.
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    Integrating Occlusion Culling into LOD on GPU
    (The Eurographics Association, 2014) Peng, Chao; John Keyser and Young J. Kim and Peter Wonka
    Real-time rendering of complex 3D models is still a very challenging task. Recently, GPU-based level-of-detail (LOD) approaches have been proposed to fast decrease the complexity of a 3D model, but applying only LOD approaches is usually not sufficient to achieve highly interactive rendering rate for the complex model that contains hundreds of millions of triangles. Visibility culling, especially occlusion culling, needs to be introduced to further reduce the amount of triangles being rendered at each frame. In this paper, we present a novel rendering approach that seamlessly integrates occlusion culling with the LOD approach in a unified scheme towards the GPU architecture. The result shows that the integration significantly reduces the complexity of the 3D model and satisfies the demands of both memory efficiency and performance.
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    Projecting Points onto Planar Parametric Curves by Local Biarc Approximation
    (The Eurographics Association, 2014) Song, Hai-Chuan; Shi, Kan-Le; Yong, Jun-Hai; Zhang, Sen; John Keyser and Young J. Kim and Peter Wonka
    This paper proposes a geometric iteration algorithm for computing point projection and inversion on surfaces based on local biarc approximation. The iteration begins with initial estimation of the projection of the prescribed test point. For each iteration, we construct a 3D biarc on the original surface to locally approximate the original surface starting from the current projection point. Then we compute the projection point for the next iteration, as well as the parameter corresponding to it, by projecting the test point onto this biarc. The iterative process terminates when the projection point satisfies the required precision. Examples demonstrate that our algorithm converges faster and is less dependent on the choice of the initial value compared to the traditional geometric iteration algorithms based on single-point approximation.