? 基于视频重建与欧拉模型紧密耦合的流体仿真
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Journal of Computer Science and Technology 2018, Vol. 33 Issue (3) :452-462    DOI: 10.1007/s11390-018-1830-7
Special Section of CVM 2018 << Previous Articles | Next Articles >>
基于视频重建与欧拉模型紧密耦合的流体仿真
Feng-Yu Li1, Chang-Bo Wang1,*, Member, CCF, Hong Qin2, Member, IEEE, Hong-Yan Quan1
1 School of Computer Science and Software Engineering, East China Normal University, Shanghai 200062, China;
2 Department of Computer Science, State University of New York at Stony Brook, NY 11794-4400, U. S. A
Augmented Flow Simulation based on Tight Coupling between Video Reconstruction and Eulerian Models
Feng-Yu Li1, Chang-Bo Wang1,*, Member, CCF, Hong Qin2, Member, IEEE, Hong-Yan Quan1
1 School of Computer Science and Software Engineering, East China Normal University, Shanghai 200062, China;
2 Department of Computer Science, State University of New York at Stony Brook, NY 11794-4400, U. S. A

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摘要 视频数据与纯物理仿真相结合的混合方法,近年来在计算机图形学中得到了广泛的应用。主要是希望保留数据驱动方法和以模型为中心的数值模拟的优势,同时克服两者的困难。欧拉方法广泛应用于流体仿真中,将速度和密度等变量存储在标准笛卡尔网格上,可以与同一场景上的视频数据相关联。本文提出了一种新的流体仿真方法,将视频重建与基于物理的仿真紧密结合,并在重仿真过程中充分利用有意义的物理属性。首先,我们从单视点视频重建出流体的密度场。第二,把密度场作为先验条件来估计流体的三维速度场。在迭代优化过程中,压力投影项可以被视为物理约束,并利用欧拉框架中解得的速度场修正每一步的结果。第三,利用重建的密度场和速度场来指导欧拉模拟,并获得可控的新结果。通过视频数据的引导,我们的场景与数据采集中的真实场景相匹配。此外,在多重网格欧拉模拟中,我们可以产生新的仿真效果,而这些效果是不能从原始视频中获得的,其目的是得到更多符合真实物理属性的新效果。最后,用几种动画示例演示了本文混合方法的显著优势。
关键词视频重建   速度估计   流体仿真   体积建模与重仿真     
Abstract: Hybrid approaches such as combining video data with pure physics-based simulation have been popular in the recent decade for computer graphics. The key motivation is to clearly retain salient advantages from both data-driven method and model-centric numerical simulation, while overcoming certain difficulties of both. The Eulerian method, which has been widely employed in flow simulation, stores variables such as velocity and density on regular Cartesian grids, so it could be associated with (volumetric) video data on the same domain. This paper proposes a novel method for flow simulation, that is tightly coupling video-based reconstruction with physically-based simulation and making use of meaningful physical attributes during re-simulation. First, we reconstruct the density field from a single-view video. Second, we estimate the velocity field using the reconstructed density field as prior. In the iterative process, the pressure projection can be treated as a physical constraint and the results of each step are corrected by obtained velocity field in the Eulerian framework. Third, we use the reconstructed density field and velocity field to guide the Eulerian simulation with anticipated new results. Through the guidance of video data, we can produce new flows that closely match with the real scene exhibited in data acquisition. Moreover, in the multigrid Eulerian simulation, we can generate new visual effects which can't be created from raw video acquisition, with a goal of easily producing many more visually interesting results and respecting true physical attributes at the same time. We demonstrate salient advantages of our hybrid method with a variety of animation examples.
KeywordsVideo Reconstruction   Velocity Estimation   Fluid Simulation   Volume Modeling and Re-simulation     
Received 2018-01-08;
本文基金:

This work was supported by the National Natural Science Foundation of China under Grant Nos. 61532002, 61672237, 61672077 and 61672149, the Natural Science Foundation of USA under Grant Nos. IIS-1715985, IIS-0949467, IIS-1047715, and IIS-1049448, and the National High Technology Research and Development 863 Program of China under Grant No. 2015AA016404.

通讯作者: Chang-Bo Wang     Email: cbwang@sei.ecnu.edu.cn
About author: Feng-Yu Li is a graduate student of School of Computer Science and Software Engineering, East China Normal University, Shanghai. He received his B.E. degree in communication engineering from Zhengzhou University, Zhengzhou. His research interest is fluid simulation based on physics and video-based reconstruction.
引用本文:   
Feng-Yu Li, Chang-Bo Wang, Hong Qin, Hong-Yan Quan.基于视频重建与欧拉模型紧密耦合的流体仿真[J]  Journal of Computer Science and Technology , 2018,V33(3): 452-462
Feng-Yu Li, Chang-Bo Wang, Hong Qin, Hong-Yan Quan.Augmented Flow Simulation based on Tight Coupling between Video Reconstruction and Eulerian Models[J]  Journal of Computer Science and Technology, 2018,V33(3): 452-462
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