论文标题
虚拟弹性对象
Virtual Elastic Objects
论文作者
论文摘要
我们介绍虚拟弹性对象（VEO）：虚拟对象，不仅看起来像他们的现实世界对应物，而且在受到新颖互动的情况下也表现得像它们一样。实现这一目标提出了多种挑战：不仅必须捕获对象，包括作用于它们的物理力，然后忠实地重建和渲染，而且还发现了合理的材料参数。为了创建VEO，我们构建了一个多视图捕获系统，该系统在压缩空气流的影响下捕获对象。在无模型，动态神经辐射场的最新进展的基础上，我们重建对象和相应的变形场。我们建议使用基于粒子的模拟器使用这些变形字段来找到代表性的材料参数，从而使我们能够运行新的模拟。为了渲染模拟对象，我们设计了一种将模拟结果与神经辐射场集成的方法。所得的方法适用于多种情况：它可以处理由形状截然不同的不均匀材料组成的对象，并且可以模拟与其他虚拟对象的相互作用。我们使用在各种力场下的12个对象的新收集的数据集提出了结果，这些数据将与社区共享。
We present Virtual Elastic Objects (VEOs): virtual objects that not only look like their real-world counterparts but also behave like them, even when subject to novel interactions. Achieving this presents multiple challenges: not only do objects have to be captured including the physical forces acting on them, then faithfully reconstructed and rendered, but also plausible material parameters found and simulated. To create VEOs, we built a multi-view capture system that captures objects under the influence of a compressed air stream. Building on recent advances in model-free, dynamic Neural Radiance Fields, we reconstruct the objects and corresponding deformation fields. We propose to use a differentiable, particle-based simulator to use these deformation fields to find representative material parameters, which enable us to run new simulations. To render simulated objects, we devise a method for integrating the simulation results with Neural Radiance Fields. The resulting method is applicable to a wide range of scenarios: it can handle objects composed of inhomogeneous material, with very different shapes, and it can simulate interactions with other virtual objects. We present our results using a newly collected dataset of 12 objects under a variety of force fields, which will be shared with the community.
