Rainbow Particle Imaging Velocimetry for Dense 3D Fluid Velocity Imaging

被引:58
|
作者
Xiong, Jinhui [1 ]
Idoughi, Ramzi [1 ]
Aguirre-Pablo, Andres A. [1 ]
Aljedaani, Abdulrahman B. [1 ]
Dun, Xiong [1 ]
Fu, Qiang [1 ]
Thoroddsen, Sigurdur T. [1 ]
Heidrich, Wolfgang [1 ]
机构
[1] King Abdullah Univ Sci & Technol, Al Khwarizmi Bldg 1,Rm 2113, Thuwal 239556900, Saudi Arabia
来源
ACM TRANSACTIONS ON GRAPHICS | 2017年 / 36卷 / 04期
关键词
Fluid velocity imaging; Rainbow PIV; Optimization; FLOW;
D O I
10.1145/3072959.3073662
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Despite significant recent progress, dense, time-resolved imaging of complex, non-stationary 3D flow velocities remains an elusive goal. In this work we tackle this problem by extending an established 2D method, Particle Imaging Velocimetry, to three dimensions by encoding depth into color. The encoding is achieved by illuminating the flow volume with a continuum of light planes (a "rainbow"), such that each depth corresponds to a specific wavelength of light. A diffractive component in the camera optics ensures that all planes are in focus simultaneously. With this setup, a single color camera is sufficient for tracking 3D trajectories of particles by combining 2D spatial and 1D color information. For reconstruction, we derive an image formation model for recovering stationary 3D particle positions. 3D velocity estimation is achieved with a variant of 3D optical flow that accounts for both physical constraints as well as the rainbow image formation model. We evaluate our method with both simulations and an experimental prototype setup.
引用
收藏
页数:14
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