Experiments in Fluids

, 51:1465 | Cite as

Toward real-time particle tracking using an event-based dynamic vision sensor

  • David DrazenEmail author
  • Patrick Lichtsteiner
  • Philipp Häfliger
  • Tobi Delbrück
  • Atle Jensen


Optically based measurements in high Reynolds number fluid flows often require high-speed imaging techniques. These cameras typically record data internally and thus are limited by the amount of onboard memory available. A novel camera technology for use in particle tracking velocimetry is presented in this paper. This technology consists of a dynamic vision sensor in which pixels operate in parallel, transmitting asynchronous events only when relative changes in intensity of approximately 10% are encountered with a temporal resolution of 1 μs. This results in a recording system whose data storage and bandwidth requirements are about 100 times smaller than a typical high-speed image sensor. Post-processing times of data collected from this sensor also increase to about 10 times faster than real time. We present a proof-of-concept study comparing this novel sensor with a high-speed CMOS camera capable of recording up to 2,000 fps at 1,024 × 1,024 pixels. Comparisons are made in the ability of each system to track dense (ρ >1 g/cm3) particles in a solid–liquid two-phase pipe flow. Reynolds numbers based on the bulk velocity and pipe diameter up to 100,000 are investigated.


Particle Image Velocimetry Particle Tracking Light Sheet Particle Tracking Velocimetry Particle List 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was partially funded by the Research Council of Norway via "Strategic Institute Project ES132014, Droplet Transport Modeling and Generation Enhancement in Hydrocarbon Multiphase Transport". Svein Vesterby provided invaluable help in setting up and maintaining the test apparatus in the Hydrodynamics laboratory at the University of Oslo.


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Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • David Drazen
    • 1
    • 4
    Email author
  • Patrick Lichtsteiner
    • 2
  • Philipp Häfliger
    • 3
  • Tobi Delbrück
    • 2
  • Atle Jensen
    • 1
  1. 1.Department of MathematicsUniversity of Oslo OsloNorway
  2. 2.Institute of NeuroinformaticsUniversity of Zürich and ETH ZürichZürichSwitzerland
  3. 3.Department of InformaticsUniversity of OsloOsloNorway
  4. 4.Naval Surface Warfare Center, Carderock DivisionWest BethesdaUSA

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