Rainbow Particle Imaging Velocimetry for Dense 3D Fluid Velocity Imaging
dc.contributor.author | Xiong, Jinhui | |
dc.contributor.author | Idoughi, Ramzi | |
dc.contributor.author | Aguirre-Pablo, Andres A. | |
dc.contributor.author | Aljedaani, Abdulrahman Barakat | |
dc.contributor.author | Dun, Xiong | |
dc.contributor.author | Fu, Qiang | |
dc.contributor.author | Thoroddsen, Sigurdur T | |
dc.contributor.author | Heidrich, Wolfgang | |
dc.date.accessioned | 2017-05-31T11:53:47Z | |
dc.date.available | 2017-05-31T11:53:47Z | |
dc.date.issued | 2017-04-11 | |
dc.identifier.uri | http://hdl.handle.net/10754/623948 | |
dc.description.abstract | 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. 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. | |
dc.title | Rainbow Particle Imaging Velocimetry for Dense 3D Fluid Velocity Imaging | |
dc.type | Poster | |
dc.contributor.department | Computational Imaging Group | |
dc.contributor.department | Computer Science Program | |
dc.contributor.department | Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division | |
dc.contributor.department | High-Speed Fluids Imaging Laboratory | |
dc.contributor.department | Mechanical Engineering Program | |
dc.contributor.department | Physical Science and Engineering (PSE) Division | |
dc.contributor.department | Visual Computing Center (VCC) | |
dc.conference.date | April 10-12, 2017 | |
dc.conference.name | KAUST Research Conference 2017: Visual Computing – Modeling and Reconstruction | |
dc.conference.location | KAUST | |
kaust.person | Xiong, Jinhui | |
kaust.person | Idoughi, Ramzi | |
kaust.person | Aguirre-Pablo, Andres | |
kaust.person | Aljedaani, Abdulrahman Barakat | |
kaust.person | Dun, Xiong | |
kaust.person | Fu, Qiang | |
kaust.person | Thoroddsen, Sigurdur T. | |
kaust.person | Heidrich, Wolfgang | |
refterms.dateFOA | 2018-06-13T18:43:04Z |
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Physical Science and Engineering (PSE) Division
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Computer Science Program
For more information visit: https://cemse.kaust.edu.sa/cs -
Mechanical Engineering Program
For more information visit: https://pse.kaust.edu.sa/study/academic-programs/mechanical-engineering/Pages/home.aspx -
Visual Computing Center (VCC)
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Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
For more information visit: https://cemse.kaust.edu.sa/ -
KAUST Research Conference 2017: Visual Computing – Modeling and Reconstruction