3D Fluid Flow Reconstruction Using Compact Light Field PIV

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12361)


Particle Imaging Velocimetry (PIV) estimates the fluid flow by analyzing the motion of injected particles. The problem is challenging as the particles lie at different depths but have similar appearances. Tracking a large number of moving particles is particularly difficult due to the heavy occlusion. In this paper, we present a PIV solution that uses a compact lenslet-based light field camera to track dense particles floating in the fluid and reconstruct the 3D fluid flow. We exploit the focal symmetry property in the light field focal stacks for recovering the depths of similar-looking particles. We further develop a motion-constrained optical flow estimation algorithm by enforcing the local motion rigidity and the Navier-Stoke fluid constraint. Finally, the estimated particle motion trajectory is used to visualize the 3D fluid flow. Comprehensive experiments on both synthetic and real data show that using a compact light field camera, our technique can recover dense and accurate 3D fluid flow.


Volumetric flow reconstruction Particle Imaging Velocimetry (PIV) Light field imaging Focal stack 


This work is partially supported by the National Science Foundation (NSF) under Grant CBET-1706130 and CRII-1948524, and the Louisiana Board of Regent under Grant LEQSF (2018-21)-RD-A-10.

Supplementary material

504471_1_En_8_MOESM1_ESM.pdf (113 kb)
Supplementary material 1 (pdf 112 KB)

Supplementary material 2 (avi 56452 KB)


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.University of DelawareNewarkUSA
  2. 2.DGeneBaton RougeUSA
  3. 3.ShanghaiTech UniversityShanghaiChina
  4. 4.Louisiana State UniversityBaton RougeUSA

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