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引用次数: 60

摘要

分析可见性算法,例如计算细分网格来表示阴影的方法,是出了名的不鲁棒性和难以在实践中使用。本文提出了一种基于广义极值刺线定义的新方法,即阴影边界的极值刺线。我们处理包含退化配置(例如共线或共面)的多个边或顶点的场景。我们引入了一种鲁棒的ε方法来确定每个广义极值刺线是否被这些场景元素阻塞或接触,从而添加到线的生成器中。我们为小于ε的多边形开发了鲁棒的阻塞谓词。当ε值较大时,小的阴影特征合并并最终消失。因此,我们可以鲁棒地连接简并场景中的广义极值刺线来形成阴影边界。我们证明了我们的方法是一致的,当特征合并时,阴影边界的连通性是保留的。我们已经实现了我们的算法,并表明我们可以鲁棒地计算解析阴影边界,达到我们选择的ε阈值的精度,对于包含许多退化的非平凡模型。
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Robust epsilon visibility
Analytic visibility algorithms, for example methods which compute a subdivided mesh to represent shadows, are notoriously unrobust and hard to use in practice. We present a new method based on a generalized definition of extremal stabbing lines, which are the extremities of shadow boundaries. We treat scenes containing multiple edges or vertices in degenerate configurations, (e.g., collinear or coplanar). We introduce a robust ε method to determine whether each generalized extremal stabbing line is blocked, or is touched by these scene elements, and thus added to the line's generators. We develop robust blocker predicates for polygons which are smaller than ε. For larger ε values, small shadow features merge and eventually disappear. We can thus robustly connect generalized extremal stabbing lines in degenerate scenes to form shadow boundaries. We show that our approach is consistent, and that shadow boundary connectivity is preserved when features merge. We have implemented our algorithm, and show that we can robustly compute analytic shadow boundaries to the precision of our chosen ε threshold for non-trivial models, containing numerous degeneracies.
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Session details: 3D acquisition and image based rendering Session details: Geometry Session details: Soft things Session details: Lighting and appearance Session details: Images and video
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