Abstract
Variational Optical Flow estimation models have proven to be highly useful tools for both tracking (rigid) object paths and for calculating motion fields registered in digital video sequences. Specific acquisition techniques, such as infrared thermographic video, allow to carry out further studies of the fluid dynamics for several kind of phenomena. This paper presents a methodological approach to obtain a reliable estimation of the temporal evolution of thermal structures in fluid surfaces using a multiresolution scheme based on the Galerkin-Wavelet Analysis. An appropriate regularizer, adapted for the specific problem herein presented, is also introduced.
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References
Horn, B.K.P., Schunck, B.G.: Determining optical flow. Artif. Intell. 17, 185–203 (1981)
Aubert, G., Deriche, R., Kornprobst, P.: Computing optical flow via variational techniques. SIAM Journal on Applied Mathematics 60, 156–182 (2000)
Bruhn, A., Weickert, J., Schnörr, C.: Lucas/kanade meets horn/schunck: combining local and global optic flow methods. Int. J. Comput. Vision 61(3), 211–231 (2005)
Suter, D.: Motion estimation and vector splines. In: CVPR 1994, pp. 939–942 (1994)
Ruhnau, P., Stahl, A., Schnorr, C.: On-line variational estimation of dynamical fluid flows with physics-based spatio-temporal regularization. In: Franke, K., Müller, K.-R., Nickolay, B., Schäfer, R. (eds.) DAGM 2006. LNCS, vol. 4174, pp. 444–454. Springer, Heidelberg (2006)
Francomano, E., Tortorici, A., Calderone, V.: Regularization of optical flow with m-band wavelet transform. Computers and Mathematics with Applications 45, 437–452 (2003)
Mémin, E., Pérez, P.: A multigrid approach for hierarchical motion estimation. In: Proc. Int. Conf. Computer Vision, pp. 933–938 (1998)
Arigovindan, M., Sühling, M., Jansen, C.P., Hunziker, P., Unser, M.: Full flow/motion-field recovery from pulsed-wave ultrasound doppler data. In: Proceedings of the 2006 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp. 213–216 (2006)
Corpetti, T., Mémin, E., Pérez, P.: Dense estimation of fluid flows. IEEE Trans. Pattern Anal. Mach. Intell. 24, 365–380 (2002)
Corpetti, T., Heitz, D., Arroyo, G., Mémin, E., Santa-Cruz, A.: Fluid experimental flow estimation based on an optical-flow scheme. Int. J. Experiments in Fluid 40, 80–97 (2006)
Varzhanskaya, T.S.: Boundary condition formulation for viscous fluid flow problems. Fluid Dynamics 4, 97–98 (2005)
Chen, L.F., Lin, J.C., Liao, H.Y.M.: Wavelet-based optical flow estimation. ICPR 03, 7068 (2000)
Oslick, M., Linscott, I., Maslakovic, S., Twicken, J.: Computing derivatives of scaling functions and wavelets. In: Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis, Pittsburgh, PA, USA, pp. 357–360 (1998)
Latto, A., Resnikoff, A.H.L., Tenenbaum, A.E.: The evaluation of connection coefficients of compactly supported wavelets. In: Proceedings of the French-USA Workshop on Wavelets and Turbulence. Springer, New York (1991)
Bindal, A., Khinast, J.G., Ierapetritou, M.G.: Adaptative multiscale solution of dynamical systems in chemical processes using wavelets. Computer and Chemical Engineering 27, 131–142 (2003)
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Franco, H., Perea, Á., Romero, E., Rodríguez, D. (2008). Fluid Flow Measurement in Thermographic Video Sequences by Wavelet-Multiresolution Optical Flow Estimation. In: Blanc-Talon, J., Bourennane, S., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2008. Lecture Notes in Computer Science, vol 5259. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88458-3_28
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DOI: https://doi.org/10.1007/978-3-540-88458-3_28
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