Skip to main content

Non-iterative double-frame 2D/3D particle tracking velocimetry


In recent years, the detection of individual particle images and their tracking over time to determine the local flow velocity has become quite popular for planar and volumetric measurements. Particle tracking velocimetry has strong advantages compared to the statistical analysis of an ensemble of particle images by means of cross-correlation approaches, such as particle image velocimetry. Tracking individual particles does not suffer from spatial averaging and therefore bias errors can be avoided. Furthermore, the spatial resolution can be increased up to the sub-pixel level for mean fields. A maximization of the spatial resolution for instantaneous measurements requires high seeding concentrations. However, it is still challenging to track particles at high seeding concentrations, if no time series is available. Tracking methods used under these conditions are typically very complex iterative algorithms, which require expert knowledge due to the large number of adjustable parameters. To overcome these drawbacks, a new non-iterative tracking approach is introduced in this letter, which automatically analyzes the motion of the neighboring particles without requiring to specify any parameters, except for the displacement limits. This makes the algorithm very user friendly and also offers unexperienced users to use and implement particle tracking. In addition, the algorithm enables measurements of high speed flows using standard double-pulse equipment and estimates the flow velocity reliably even at large particle image densities.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4


  • Cierpka C, Lütke B, Kähler CJ (2013) Higher order multi-frame particle tracking velocimetry. Exp Fluids 54(5):1533

    Article  Google Scholar 

  • Elsinga GE, Westerweel J, Scarano F, Novara M (2011) On the velocity of ghost particles and the bias errors in tomographic-PIV. Exp Fluids 50(4):825–838

    Article  Google Scholar 

  • Fuchs T, Hain R, Kähler CJ (2016) Double-frame 3D-PTV using a tomographic predictor. Exp Fluids 57(11):174

    Article  Google Scholar 

  • Kähler CJ, Scharnowski S, Cierpka C (2012a) On the resolution limit of digital particle image velocimetry. Exp Fluids 52(6):1629–1639

    Article  Google Scholar 

  • Kähler CJ, Scharnowski S, Cierpka C (2012b) On the uncertainty of digital PIV and PTV near walls. Exp Fluids 52(6):1641–1656

    Article  Google Scholar 

  • Kähler CJ, Astarita T, Vlachos PP, Sakakibara J, Hain R, Discetti S, La Foy R, Cierpka C (2016a) Main results of the 4th International PIV Challenge. Exp Fluids 57(6):97

    Article  Google Scholar 

  • Kähler CJ, Scharnowski S, Cierpka C (2016b) Highly resolved experimental results of the separated flow in a channel with streamwise periodic constrictions. J Fluid Mech 796:257–284

    Article  Google Scholar 

  • Mikheev AV, Zubtsov VM (2008) Enhanced particle-tracking velocimetry (EPTV) with a combined two-component pair-matching algorithm. Meas Sci Technol 19(8):085401

    Article  Google Scholar 

  • Novara M, Schanz D, Reuther N, Kähler CJ, Schröder A (2016) Lagrangian 3D particle tracking in high-speed flows: Shake-The-Box for multi-pulse systems. Exp Fluids 57(8):128

    Article  Google Scholar 

  • Ohmi K, Li HY (2000) Particle-tracking velocimetry with new algorithms. Meas Sci Technol 11(6):603–616

    Article  Google Scholar 

  • Okamoto K, Nishio S, Saga T, Kobayashi T (2000) Standard images for particle-image velocimetry. Meas Sci Technol 11(6):685–691

    Article  Google Scholar 

  • Schanz D, Gesemann S, Schröder A (2016) Shake-The-Box: Lagrangian particle tracking at high particle image densities. Exp Fluids 57(5):70

    Article  Google Scholar 

Download references


Financial support by the Deutsche Forschungsgemeinschaft (DFG) through Grant no. KA 1808/8-2 is gratefully acknowledged by the authors.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Thomas Fuchs.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Fuchs, T., Hain, R. & Kähler, C.J. Non-iterative double-frame 2D/3D particle tracking velocimetry. Exp Fluids 58, 119 (2017).

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: