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A New Algorithm for the Evaluation of PTV Data Using Point Matching Distance Mesaures and Deterministic Annealing
Citation key Kuzmanovski1998
Author Kuzmanovski, A. and Stellmacher, M. and Obermayer, K.
Title of Book Proc. Int. Symp. on Appl. of Laser Techniques to Fluid Mechanics
Pages 10.4.1 – 10.4.6
Year 1998
Abstract We describe a new method for the evaluation of single pulse multiple exposure PTV data which allows the joint estimate of several local flow field parameters, among them components describing local translation, rotation and shear. The method operates on particle coordinates, which can be extracted from digital images using the CLEAN algorithm (Schwarz 1978), and is based on an algorithm recently proposed by Gold et al. (Gold, Rangarajan and Mjolsness, Neur. Comp. 8, 1996) for matching problems in stereo vision and statistical pattern recognition. For flows with small velocity gradients our method compares favorable to crosscorrelation techniques. When velocity gradients become larger, for example near vortices and in shear flows, the new method leads to strongly improved velocity estimates, and additionally allows an estimate of the strength of the local rotation and shear components. The method can in principle be extended to stereo data, because computational expenses grow linearly with the the number of particle coordinates only.
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