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Updated: Aug 7, 2026

High-speed Particle Image Velocimetry Near Surfaces
Published on: June 24, 2013
Non-Gaussian velocity distributions integrated over space, time, and scales
Volker Willert1, Julian Eggert, Jürgen Adamy
1Darmstadt University of Technology, Institute for Automatic Control, Control Theory and Robotics Lab, Darmstadt D-64283, Germany. volker@rtr.tu-darmstadt.de
Abstract:
Velocity distributions are an enhanced representation of image velocity containing more velocity information than velocity vectors. In particular, non-Gaussian velocity distributions allow for the representation of ambiguous motion information caused by the aperture problem or multiple motions at motion boundaries. To resolve motion ambiguities, discrete non-Gaussian velocity distributions are suggested, which are integrated over space, time, and scales using a joint Bayesian prediction and refinement approach. This leads to a hierarchical velocity-distribution representation from which robust velocity estimates for both slow and high speeds as well as statistical confidence measures rating the velocity estimates can be computed.
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