Medial Elastics: Efficient and Collision-Ready Deformation via Medial Axis Transform
Medial Elastics: Efficient and Collision-Ready Deformation via Medial Axis Transform
复制标题
内侧弹性：通过内侧轴变换实现高效且防碰撞的变形
DOI：
10.1145/3384515
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发表时间：
2020
影响因子：
6.2
通讯作者：
Yang Yin
中科院分区：
文献类型：
--
作者：
Lan Lei;Luo Ran;Fratarcangeli Marco;Xu Weiwei;Wang Huamin;Guo Xiaohu;Yao Junfeng;Yang Yin
我们提出了一个非线性可变形物体交互仿真的框架。我们系统的主要特征是可变形模拟和碰撞剔除的无缝集成，这通常是在现有的动画系统中独立处理的。连接它们的桥梁是中轴变换（MAT），这是一种高保真的复杂3D形状的体积近似。从物理仿真的角度来看，MAT可以得到一个表达能力强、结构紧凑的简化非线性模型。我们采用了一种半简化的投影动力学公式，可以很好地捕获高分辨率模型的高频局部变形，同时保持较低的计算成本。我们的关键观察是，最引人注目的（非线性）可变形效果是由局部约束投影实现的，它不应该被积极地减少，而只在全局阶段应用模型减少。从碰撞检测(CD)/碰撞剔除（CC）的角度来看，MAT在几何上是通用的，使用线性插值球体（即所谓的中间原语（MPs））来近似输入模型的边界。两个MPs之间的相交检验被表述为一个二次约束的二次规划问题。我们给出了一种精确解决这一问题的算法，该算法返回一对相交的MPs之间的最深穿透。当与空间散列相结合时，即使在大规模模拟中，碰撞（包括自碰撞）也可以在几毫秒内有效地在GPU上识别出来。我们已经在各种几何复杂和高分辨率的可变形物体上测试了我们的系统，我们的系统产生了令人信服的动画，所有的碰撞/自碰撞都以互动的速度得到了很好的处理。
We propose a framework for the interactive simulation of nonlinear deformable objects. The primary feature of our system is the seamless integration of deformable simulation and collision culling, which are often independently handled in existing animation systems. The bridge connecting them is the medial axis transform (MAT), a high-fidelity volumetric approximation of complex 3D shapes. From the physics simulation perspective, MAT leads to an expressive and compact reduced nonlinear model. We employ a semireduced projective dynamics formulation, which well captures high-frequency local deformations of high-resolution models while retaining a low computation cost. Our key observation is that the most compelling (nonlinear) deformable effects are enabled by the local constraints projection, which should not be aggressively reduced, and only apply model reduction at the global stage. From the collision detection (CD)/collision culling (CC) perspective, MAT is geometrically versatile using linear-interpolated spheres (i.e., the so-called medial primitives (MPs)) to approximate the boundary of the input model. The intersection test between two MPs is formulated as a quadratically constrained quadratic program problem. We give an algorithm to solve this problem exactly, which returns the deepest penetration between a pair of intersecting MPs. When coupled with spatial hashing, collision (including self-collision) can be efficiently identified on the GPU within a few milliseconds even for massive simulations. We have tested our system on a variety of geometrically complex and high-resolution deformable objects, and our system produces convincing animations with all of the collisions/self-collisions well handled at an interactive rate.