Rainbow Particle Imaging Velocimetry for Dense 3D Fluid Velocity Imaging

Handle URI:
http://hdl.handle.net/10754/623948
Title:
Rainbow Particle Imaging Velocimetry for Dense 3D Fluid Velocity Imaging
Authors:
Xiong, Jinhui ( 0000-0002-1507-6070 ) ; Idoughi, Ramzi; Aguirre-Pablo, Andres; Aljedaani, Abdulrahman Barakat; Dun, Xiong; Fu, Qiang ( 0000-0001-6395-8521 ) ; Thoroddsen, Sigurdur T. ( 0000-0001-6997-4311 ) ; Heidrich, Wolfgang ( 0000-0002-4227-8508 )
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.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Conference/Event name:
KAUST Research Conference 2017: Visual Computing – Modeling and Reconstruction
Issue Date:
11-Apr-2017
Type:
Poster
Appears in Collections:
Posters; KAUST Research Conference 2017: Visual Computing – Modeling and Reconstruction

Full metadata record

DC FieldValue Language
dc.contributor.authorXiong, Jinhuien
dc.contributor.authorIdoughi, Ramzien
dc.contributor.authorAguirre-Pablo, Andresen
dc.contributor.authorAljedaani, Abdulrahman Barakaten
dc.contributor.authorDun, Xiongen
dc.contributor.authorFu, Qiangen
dc.contributor.authorThoroddsen, Sigurdur T.en
dc.contributor.authorHeidrich, Wolfgangen
dc.date.accessioned2017-05-31T11:53:47Z-
dc.date.available2017-05-31T11:53:47Z-
dc.date.issued2017-04-11-
dc.identifier.urihttp://hdl.handle.net/10754/623948-
dc.description.abstractDespite 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.en
dc.titleRainbow Particle Imaging Velocimetry for Dense 3D Fluid Velocity Imagingen
dc.typePosteren
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.conference.dateApril 10-12, 2017en
dc.conference.nameKAUST Research Conference 2017: Visual Computing – Modeling and Reconstructionen
dc.conference.locationKAUSTen
kaust.authorXiong, Jinhuien
kaust.authorIdoughi, Ramzien
kaust.authorAguirre-Pablo, Andresen
kaust.authorAljedaani, Abdulrahman Barakaten
kaust.authorDun, Xiongen
kaust.authorFu, Qiangen
kaust.authorThoroddsen, Sigurdur T.en
kaust.authorHeidrich, Wolfgangen
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