Interactive Continuous Collision Detection for Topology Changing Models Using Dynamic Clustering.

Liang He, Ricardo Ortiz, Andinet Enquobahrie, Dinesh Manocha
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引用次数: 15

Abstract

We present a fast algorithm for continuous collision detection between deformable models. Our approach performs no precomputation and can handle general triangulated models undergoing topological changes. We present a fast decomposition algorithm that represents the mesh boundary using hierarchical clusters and only needs to perform inter-cluster collision checks. The key idea is to compute such clusters quickly and merge them to generate a dynamic bounding volume hierarchy. The overall approach reduces the overhead of computing the hierarchy and also reduces the number of false positives. We highlight the the algorithm's performance on many complex benchmarks generated from medical simulations and crash analysis. In practice, we observe 1.4 to 5 times speedup over prior CCD algorithms for deformable models in our benchmarks.

Abstract Image

Abstract Image

基于动态聚类的拓扑变化模型交互式连续碰撞检测。
提出了一种快速的可变形模型间连续碰撞检测算法。我们的方法不需要预先计算,并且可以处理发生拓扑变化的一般三角模型。我们提出了一种快速分解算法,该算法使用分层簇表示网格边界,并且只需要执行簇间碰撞检查。关键思想是快速计算这些集群并合并它们以生成动态边界卷层次结构。总体方法减少了计算层次结构的开销,也减少了误报的数量。我们强调了该算法在许多复杂的基准上的性能,这些基准是由医学模拟和崩溃分析产生的。在实践中,我们观察到在我们的基准测试中,可变形模型的CCD算法比先前的CCD算法加速1.4到5倍。
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