A New Algorithm for the Interrogation of 3D Holographic Particle Tracking Velocimetry Data Based on Deterministic Annealing and EM-Optimization

Abstract

Recently we have presented a new particle tracking algorithm for the interrogation of PTV data [Kuzmanowski et al., 1998], [Stellmacher and Obermayer, 1999]. This procedure is based on an algorithm recently proposed by [Gold et al., 1998] for solving point matching problems in statistical pattern recognition, which estimates correspondences between particles in two PTV frames and the local flow field parameter simultaneously. The new method has two advantages: (1) It allows to determine not only local velocity, but also other local components of the flow field like rotation and shear, and (2) it allows to reliably determine flow-field parameters also in regions of high velocity gradients (e.g. vortices or shear flow). In this contribution we extend this algorithm to be applied to the interrogation of 3D holographic PIV data. Benchmarks with cross-correlation and nearest neighbor methods show, that the algorithm remains the superior performance which we have observed for the 2D case. Be..