PIV-Based 3D Fluid Flow Reconstruction Using Light Field Camera

Particle Imaging Velocimetry (PIV) estimates the flow of fluid by analyzing the motion of injected particles. The problem is challenging as the particles lie at different depths but have similar appearance and tracking a large number of particles is particularly difficult. In this paper, we present a PIV solution that uses densely sampled light field to reconstruct and track 3D particles. We exploit the refocusing capability and focal symmetry constraint of the light field for reliable particle depth estimation. We further propose a new motion-constrained optical flow estimation scheme by enforcing local motion rigidity and the Navier-Stoke constraint. Comprehensive experiments on synthetic and real experiments show that using a single light field camera, our technique can recover dense and accurate 3D fluid flows in small to medium volumes.

[1]  Marcus A. Magnor,et al.  Image-based tomographic reconstruction of flames , 2004, SIGGRAPH '04.

[2]  Jingyi Yu,et al.  Reconstructing Gas Flows Using Light-Path Approximation , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[3]  C. Brücker.  3D scanning PIV applied to an air flow in a motored engine using digital high-speed video , 1997 .

[4]  Yi Li,et al.  Data exploration of turbulence simulations using a database cluster , 2007, Proceedings of the 2007 ACM/IEEE Conference on Supercomputing (SC '07).

[5]  Konrad Schindler,et al.  Volumetric Flow Estimation for Incompressible Fluids Using the Stationary Stokes Equations , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[6]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[7]  C. Willert,et al.  Three-dimensional particle imaging with a single camera , 1992 .

[8]  Joseph R. Nielson,et al.  Determining 3D Flow Fields via Multi-camera Light Field Imaging , 2013, Journal of visualized experiments : JoVE.

[9]  Yi Li,et al.  A public turbulence database cluster and applications to study Lagrangian evolution of velocity increments in turbulence , 2008, 0804.1703.

[10]  Jun Sakakibara,et al.  High-speed scanning stereoscopic PIV for 3D vorticity measurement in liquids , 2004 .

[11]  Wolfgang Heidrich,et al.  Reconfigurable rainbow PIV for 3D flow measurement , 2018, 2018 IEEE International Conference on Computational Photography (ICCP).

[12]  Christoph Schnörr,et al.  Variational fluid flow measurements from image sequences: synopsis and perspectives , 2010 .

[13]  Qionghai Dai,et al.  Transparent Object Reconstruction via Coded Transport of Intensity , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[14]  Hans-Peter Seidel,et al.  Time-resolved 3d capture of non-stationary gas flows , 2008, SIGGRAPH Asia '08.

[15]  Ajay K. Prasad,et al.  Stereoscopic particle image velocimetry , 2000 .

[16]  Andres A. Aguirre-Pablo,et al.  Tomographic Particle Image Velocimetry using Smartphones and Colored Shadows , 2017, Scientific Reports.

[17]  Paul E. Debevec,et al.  Acquisition of time-varying participating media , 2005, ACM Trans. Graph..

[18]  Brian S. Thurow,et al.  Three-Dimensional Particle Image Velocimetry Using a Plenoptic Camera , 2012 .

[19]  Jos Stam,et al.  Stable fluids , 1999, SIGGRAPH.

[20]  A. Prasad.  Particle image velocimetry , 2000 .

[21]  Bastian Goldlücke,et al.  Accurate Depth and Normal Maps from Occlusion-Aware Focal Stack Symmetry , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[22]  Brian S. Thurow,et al.  Tomographic Reconstruction of a 3-D Flow Field Using a Plenoptic Camera , 2012 .

[23]  Alexandra H. Techet,et al.  Quantitative wake analysis of a freely swimming fish using 3D synthetic aperture PIV , 2015 .

[24]  Xiong Dun,et al.  Rainbow particle imaging velocimetry for dense 3D fluid velocity imaging , 2017, ACM Trans. Graph..

[25]  Javier Sánchez Pérez,et al.  Horn-Schunck Optical Flow with a Multi-Scale Strategy , 2013, Image Process. Line.

[26]  Armin Gruen,et al.  Particle tracking velocimetry in three-dimensional flows , 1993, Experiments in Fluids.

[27]  Kiriakos N. Kutulakos,et al.  Photo-Consistent Reconstruction of Semitransparent Scenes by Density-Sheet Decomposition , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[28]  Kiriakos N. Kutulakos,et al.  Transparent and Specular Object Reconstruction , 2010, Comput. Graph. Forum.

[29]  Kiriakos N. Kutulakos,et al.  Dynamic Refraction Stereo , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[30]  Feng Li,et al.  Angular domain reconstruction of dynamic 3D fluid surfaces , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[31]  Shree K. Nayar,et al.  Compressive Structured Light for Recovering Inhomogeneous Participating Media , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[32]  Joseph Katz,et al.  Turbulent flow measurement in a square duct with hybrid holographic PIV , 1997 .

[33]  Stefan B. Williams,et al.  Decoding, Calibration and Rectification for Lenselet-Based Plenoptic Cameras , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[34]  Simon Pick,et al.  Stereoscopic PIV on multiple color-coded light sheets and its application to axial flow in flapping robotic insect wings , 2009 .

[35]  M. Pauly,et al.  Embedded deformation for shape manipulation , 2007, SIGGRAPH 2007.

[36]  Julio Soria,et al.  Towards 3C-3D digital holographic fluid velocity vector field measurement?tomographic digital holographic PIV (Tomo-HPIV) , 2008 .

[37]  A. Schröder,et al.  Shake-The-Box: Lagrangian particle tracking at high particle image densities , 2016, Experiments in Fluids.

[38]  P. Hanrahan,et al.  Light Field Photography with a Hand-held Plenoptic Camera , 2005 .

[39]  Alexandra H. Techet,et al.  Three-dimensional synthetic aperture particle image velocimetry , 2010 .

[40]  Bernhard Wieneke,et al.  Tomographic particle image velocimetry , 2006 .

[41]  Wolfgang Heidrich,et al.  From capture to simulation , 2014, ACM Trans. Graph..

[42]  J. Belden,et al.  Three-dimensional microscopic light field particle image velocimetry , 2017 .

[43]  D. Grier,et al.  Methods of Digital Video Microscopy for Colloidal Studies , 1996 .

[44]  L. Lourenço.  Particle Image Velocimetry , 1989 .

[45]  Bernhard Wieneke,et al.  Volume self-calibration for 3D particle image velocimetry , 2008 .

[46]  Frédo Durand,et al.  Refraction Wiggles for Measuring Fluid Depth and Velocity from Video , 2014, ECCV.

[47]  King-Sun Fu,et al.  IEEE Transactions on Pattern Analysis and Machine Intelligence Publication Information , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[48]  Can Chen,et al.  Depth Recovery from Light Field Using Focal Stack Symmetry , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[49]  Dana Dabiri,et al.  A full three-dimensional characterization of defocusing digital particle image velocimetry , 2005 .