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A new deformation simulation algorithm for elastic-plastic objects based on splat primitives

机译:基于Splat基元的弹塑性物体新变形仿真算法

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摘要

To achieve high computational efficiency and realistic visual effects, a new simulation algorithm for soft tissue deformation, which is based on a shape-matching scheme using splat primitives, is presented for interactive real-time applications, such as surgery simulation and video games. The most important novelty of the proposed approach lies in the fact that surface splats instead of points are employed in the computation of the deformation and fracturing of an elastic-plastic object. By controlling the sampling density and automatically adjusting the size of the circular splats, the surface of the simulated object can be seamlessly covered with a much small number of splats than points. Splats are then divided into clusters using the K-Means clustering algorithm. As a result, the elastic-plastic deformation of these clusters can be simulated using a shape-matching strategy, allowing more degrees of freedom (DOFs) in the simulation. Experimental results demonstrate that the proposed algorithm enormously reduces memory space and greatly improves computational efficiency (approximately twice in simulating plastic deformations compared with classical shape-matching methods), making it more suitable for interactive and real-time applications.
机译:为了实现高计算效率和现实的视觉效果,提供了一种用于软组织变形的新型仿真算法,其基于使用Splat基元的形状匹配方案进行交互式实时应用,例如手术模拟和视频游戏。所提出的方法中最重要的新颖性在于,在计算弹塑性物体的变形和压裂的计算中使用表面Splats而不是点。通过控制采样密度并自动调节圆形Splats的尺寸,模拟物体的表面可以用比点的少量Splats无缝地覆盖。然后使用K-means聚类算法将Splats分成群集。结果,可以使用形状匹配的策略模拟这些簇的弹性塑性变形,从而允许模拟中更多的自由度(DOF)。实验结果表明,所提出的算法极大地减少了内存空间,大大提高了计算效率(与古典形状匹配方法相比,模拟塑性变形中大约两次),使其更适合交互式和实时应用。

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