KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Computer Science Program
Visual Computing Center (VCC)
Online Publication Date2018-05-31
Print Publication Date2018-05
Permanent link to this recordhttp://hdl.handle.net/10754/630455
MetadataShow full item record
AbstractIn recent years, 3D Particle Imaging Velocimetry (PIV) has become more and more attractive due to its ability to fully characterize various fluid flows. However, 3D fluid capture and velocity field reconstruction remain a challenging problem. A recent rainbow PIV system encodes depth into color and successfully recovers 3D particle trajectories, but it also suffers from a limited and fixed volume size, as well as a relatively low light efficiency. In this paper, we propose a reconfigurable rainbow PIV system that extends the volume size to a considerable range. We introduce a parallel double-grating system to improve the light efficiency for scalable rainbow generation. A varifocal encoded diffractive lens is designed to accommodate the size of the rainbow illumination, ranging from 15 mm to 50 mm. We also propose a truncated consensus ADMM algorithm to efficiently reconstruct particle locations. Our algorithm is 5x faster compared to the state-of-the-art. The reconstruction quality is also improved significantly for a series of density levels. Our method is demonstrated by both simulation and experimental results.
CitationXiong J, Fu Q, Idoughi R, Heidrich W (2018) Reconfigurable rainbow PIV for 3D flow measurement. 2018 IEEE International Conference on Computational Photography (ICCP). Available: http://dx.doi.org/10.1109/iccphot.2018.8368475.
SponsorsThis work was supported by King Abdullah University of Science and Technology CRG Funding and Baseline Funding.
Conference/Event name2018 IEEE International Conference on Computational Photography, ICCP 2018