Two-dimensional Gaussian regression for sub-pixel displacement estimation in particle image velocimetry or particle position estimation in particle tracking velocimetry

By Holger Nobach, M. Honkanen. 2005

194 citations recorded by the source corpus.

Subfields: Computational Mechanics

View Paper: https://www.semanticscholar.org/paper/9c35733ce5021e2db51e16566e1030a7d64e3505

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

1. Misganu Debella-Gilo
2. Andreas Kääb
3. W. Thielicke
4. Eize J. Stamhuis

Citations in the corpus

• Sub-pixel precision image matching for measuring surface displacements on mass movements using normalized cross-correlation (2011, methodology): “A number of models have been tested in empirical and theoretical researches, particularly in particle image velocimetry (PIV), though with varying successes (Nobach & Honkanen, 2005; Westerweel, 1993; Willert & Gharib, 1991).”
• PIVlab – Towards User-friendly, Affordable and Accurate Digital Particle Image Velocimetry in MATLAB (2014, background): “In this case, a two-dimensional Gaussian function (9-point fit) has a better performance [25].”