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• W2761844597 abstract "We present a collision detection (CD) method for complex and large-scale fracturing models that have geometric and topological changes. We first propose a novel dual-cone culling method to improve the performance of CD, especially self-collision detection among fracturing models. Our dual-cone culling method has a small computational overhead and a conservative algorithm. Combined with bounding volume hierarchies (BVHs), our dual-cone culling method becomes approximate. However, we found that our method does not miss any collisions in the tested benchmarks. We also propose a novel, selective restructuring method that improves the overall performance of CD and reduces performance degradations at fracturing events. Our restructuring method is based on a culling efficiency metric that measures the expected number of overlap tests of a BVH. To further reduce the performance degradations at fracturing events, we also propose a novel, fast BVH construction method that builds multiple levels of the hierarchy in one iteration using a grid and hashing. We test our method with four different large-scale deforming benchmarks. Compared to the state-of-the-art methods, our method shows a more stable performance for CD by improving the performance by a factor of up to two orders of magnitude at frames when deforming models change their mesh topologies." @default.
• W2761844597 created "2017-10-20" @default.
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• W2761844597 date "2010-07-02" @default.
• W2761844597 modified "2023-09-27" @default.
• W2761844597 title "FASTCD: fracturing-aware stable collision detection" @default.
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• W2761844597 doi "https://doi.org/10.5555/1921427.1921450" @default.
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