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A Variational Approach to Adaptive Correlation for Motion Estimation in Particle Image Velocimetry

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5096))

Abstract

In particle image velocimetry (PIV) a temporally separated image pair of a gas or liquid seeded with small particles is recorded and analysed in order to measure fluid flows therein. We investigate a variational approach to cross-correlation, a robust and well-established method to determine displacement vectors from the image data. A “soft” Gaussian window function replaces the usual rectangular correlation frame. We propose a criterion to adapt the window size and shape that directly formulates the goal to minimise the displacement estimation error. In order to measure motion and adapt the window shapes at the same time we combine both sub-problems into a bi-level optimisation problem and solve it via continuous multiscale methods. Experiments with synthetic and real PIV data demonstrate the ability of our approach to solve the formulated problem. Moreover window adaptation yields significantly improved results.

This work was partially financed by the EC project FLUID (FP6-513663).

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References

  1. Raffel, M., Willert, C., Kompenhans, J.: Particle Image Velocimetry, vol. 2. Springer, Berlin (2001)

    Google Scholar 

  2. Lucas, B., Kanade, T.: An Iterative Image Registration Technique with an Application to Stereo Vision. In: Proceedings of DARPA Imaging Understanding Workshop, pp. 121–130 (1981)

    Google Scholar 

  3. Bruhn, A., Weickert, J., Schnörr, C.: Lucas/Kanade Meets Horn/Schunck: Combining Local and Global Optic Flow Methods. International Journal of Computer Vision 61(3), 211–231 (2005)

    Article  Google Scholar 

  4. Ruhnau, P., Stahl, A., Schnörr, C.: Variational Estimation of Experimental Fluid Flows with Physics-based Spatio-temporal Regularization. Measurement Science and Technology 18, 755–763 (2007)

    Article  Google Scholar 

  5. Unser, M., Aldroubi, A., Eden, M.: B-Spline Signal Processing: Part II—Efficient Design and Applications. IEEE Transactions on Signal Processing 41(2), 834–848 (1993)

    Article  MATH  Google Scholar 

  6. Stanislas, M., Okamoto, K., Kähler, C., Westerweel, J.: Third International PIV-Challenge. Exp. in Fluids (to be published, 2006)

    Google Scholar 

  7. Carlier, J., Wieneke, B.: Deliverable 1.2: Report On Production and Diffusion of Fluid Mechanic Images and Data. Activity Report, European Project FLUID Deliverable 1.2, Cemagref, LaVision (2005)

    Google Scholar 

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Gerhard Rigoll

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© 2008 Springer-Verlag Berlin Heidelberg

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Becker, F., Wieneke, B., Yuan, J., Schnörr, C. (2008). A Variational Approach to Adaptive Correlation for Motion Estimation in Particle Image Velocimetry. In: Rigoll, G. (eds) Pattern Recognition. DAGM 2008. Lecture Notes in Computer Science, vol 5096. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69321-5_34

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  • DOI: https://doi.org/10.1007/978-3-540-69321-5_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69320-8

  • Online ISBN: 978-3-540-69321-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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