Abstract
In this research project, approaches for the reliable reconstruction of flow fields from captured particle images and their visualization have been developed. One aspect has been on developing techniques that can generate a velocity field that is consistent with a selected physical fluid model. Therefore, we have introduced a model-based approach that integrates a priori knowledge of this model into the reconstruction process. Another aspect has been on the design of techniques that are capable of dealing with real-time constraints, and which thus have the potential to be used in combination with high-speed camera systems to interactively steer the reconstruction process. Programmable graphics hardware has been exploited as a co-processor for numerical computations to achieve interactivity, both for the reconstruction and visualization of generated fields. All these techniques have been verified in an experiment on living microorganisms. In the last phase of the project we have focused on the extension of the techniques towards the processing of 3D particle images and the visualization of the reconstructed flow fields.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bürger, K., Schneider, J., Kondratieva, P., Krüger, J., Westermann, R.: Interactive visual exploration of instationary 3D-flows. In: Eurographics/IEEE VGTC Symposium on Visualization (EuroVis) (2007)
Bürger, K., Kondratieva, P., Krüger, J., Westermann, R.: Importance-driven particle techniques for flow visualization. In: Proceedings of IEEE VGTC Pacific Visualization Symposium (2008)
Corpetti, T., Mémin, E., Pérez, P.: Estimating fluid optical flow. In: 15th Int. Conf. Pattern Recognition, vol. 3, pp. 1045–1048 (2000)
Corpetti, T., Heitz, D., Arroyo, G., Mémin, E., Santa-Cruz, A.: Fluid experimental flow estimation based on an optical-flow scheme. Exp. Fluids 40(1), 80–97 (2005)
Gupta, S., Prince, J.: Stochastic models for div-curl optical flow methods. Signal Proc. Lett. 3(2), 32–34 (1996)
Hackbusch, W.: Iterative Solutions of Large Sparse Systems of Equations. Springer, New York (1994)
Horn, B., Schunck, B.: Determining optical flow. Artif. Intell. 17, 185–203 (1981)
Kalmoun, E.M., Rüde, U.: A variational multigrid for computing the optical flow. In: Vision, Modeling, and Visualization Conference, pp. 577–584 (2003)
Kondratieva, P., Georgii, J., Westermann, R.: Echtzeitverfahren zur modellbasierten rekonstruktion von strömungsfeldern aus experimentell bestimmten partikelsequenzen. In: 14. GALA Fachtagung, Lasermethoden in der Strömungsmesstechnik (2006)
Kondratieva, P., Georgii, J., Petermeier, H., Kowalczyk, W., Delgado, A., Westermann, R.: A real-time model-based approach for the reconstruction of fluid flows induced by microorganisms. Experiments in Fluids 45(2), 203–222 (2008)
Krüger, J., Westermann, R.: Linear algebra operators for GPU implementation of numerical algorithms. ACM Transactions on Graphics 22(3), 908–916 (2003)
Krüger, J., Kipfer, P., Kondratieva, P., Westermann, R.: A particle system for interactive visualization of 3D flows. IEEE Transactions on Visualization and Computer Graphics 11(6), 744–756 (2005)
Mémin, E., Pérez, P.: A multigrid approach for hierarchical motion estimation. In: International Conference on Computer Vision, pp. 933–938 (1998)
Modersitzki, J.: Numerical Methods for Image Registration. Oxford university press, New York (2004)
Nakajima, Y., Inomata, H., Nogawa, H., Sato, Y., Tamura, S., Okazaki, K., Torii, S.: Physics-based flow estimation of fluids. Pattern Recognition 36(5), 1203–1212 (2003)
Nobach, H., Ouellette, N.T., Bodenschatz, E., Tropea, C.: Full-field correlation-based image processing for PIV. In: 6th International Symposium on Particle Image Velocimetry (2005)
Owens, J.D., Luebke, D., Govindaraju, N., Harris, M., Krüger, J., Lefohn, A.E., Purcell, T.J.: A survey of general-purpose computation on graphics hardware. In: Computer Graphics Forum, vol. 26, pp. 80–113 (2007)
Petermeier, H., Delgado, A., Kondratieva, P., Westermann, R., Holtmann, F., Krishnamachari, V., Denz, C.: A hybrid approach between experiment and evaluation for artefact detection and flow field reconstruction. In: 12th International Symposium on Flow Visualization (2006)
Post, F.H., Vrolijk, B., Hauser, H., Laramee, R.S., Doleisch, H.: The state of the art in flow visualisation: Feature extraction and tracking. Computer Graphics Forum 22(4), 775–792 (2003)
Quenot, G.M., Pakleza, J.D., Kowalewski, T.A.: Particle image velocimetry with optical flow. Exp. Fluids 25(3), 177–189 (1998)
Raffel, M., Willert, C.E., Kompenhans, J.: Particle image velocimetry: A practical guide, 2nd edn. Springer, Heidelberg (2001)
Ruhnau, P., Schnörr, C.: Optical stokes flow estimation: An imaging-based control approach. Exp. Fluids 42(1), 61–78 (2007)
Ruhnau, P., Kohlberger, T., Schnörr, C., Nobach, H.: Variational optical flow estimation for particle image velocimetry. Exp. Fluids 38(1), 21–32 (2005)
Scarano, F.: Iterative image deformation methods in PIV. Meas. Sci. and Technol. 13(1), R1–R19 (2002)
Schiwietz, T., Westermann, R.: Gpu-piv. In: Vision, Modeling and Visualization 2004 (2004)
Westerweel, J.: Digital particle image velocimetry: Theory and application. PhD thesis, Delft University of Technology (1993)
Willert, C., Gharib, M.: Digital particle image velocimetry. Exp. Fluids 10(4), 181–193 (1991)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kondratieva, P., Bürger, K., Georgii, J., Westermann, R. (2009). Real-Time Approaches for Model-Based PIV and Visual Fluid Analysis. In: Nitsche, W., Dobriloff, C. (eds) Imaging Measurement Methods for Flow Analysis. Notes on Numerical Fluid Mechanics and Multidisciplinary Design, vol 106. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01106-1_26
Download citation
DOI: https://doi.org/10.1007/978-3-642-01106-1_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01105-4
Online ISBN: 978-3-642-01106-1
eBook Packages: EngineeringEngineering (R0)