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Distortion Compensation for Generalized Stereoscopic Particle Image Velocimetry

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TLDR
In this paper, a general experimental calibration procedure is described which determines the magnification matrix of a distorted imaging system, and an algorithm is presented to compute accurate velocity field displacements from measurements of distorted PIV images.
Abstract
Optical distortion due to inaccurate optical alignment, lens nonlinearity, and/or refraction by optical windows, fluid interfaces, and other optical elements of an experiment causes inaccuracy by introducing variable magnification. Since fractional changes in the magnification have a one-to-one effect on the accuracy of measuring the velocity, it is important to compensate for such distortions. A general experimental calibration procedure is described which determines the magnification matrix of a distorted imaging system, and an algorithm is presented to compute accurate velocity field displacements from measurements of distorted PIV images. These procedures form a basis for generalized stereoscopic PIV procedures which permit easy electronic registration of multiple cameras and accurate recombination of stereoscopic displacement fields to obtain the three-dimensional velocity vector field.

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Citations
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Twenty years of particle image velocimetry

TL;DR: The development of the method of particle image velocimetry (PIV) is traced by describing some of the milestones that have enabled new and/or better measurements to be made.
Journal ArticleDOI

Tomographic particle image velocimetry

TL;DR: In this paper, a tomographic particle image velocimetry (tomographic-PIV) system based on the illumination, recording and reconstruction of tracer particles within a 3D measurement volume is described.
Journal ArticleDOI

Tomographic PIV: principles and practice

TL;DR: A survey of the major developments in 3D velocity field measurements using the tomographic particle image velocimetry (PIV) technique is given in this article, where the fundamental aspects of the technique are discussed beginning from hardware considerations for volume illumination, imaging systems, their configurations and system calibration.
Journal ArticleDOI

Volume self-calibration for 3D particle image velocimetry

TL;DR: In this article, a volumetric self-calibration technique was developed based on the computation of the 3D position of matching particles by triangulation as in 3D-PTV.
Journal ArticleDOI

Stereo-PIV using self-calibration on particle images

TL;DR: In this paper, a stereo-PIV calibration procedure is developed based on fitting a camera pinhole model to the two cameras using single or multiple views of a 3D calibration plate, and a disparity vector map is computed on real particle images by cross-correlation of the images from cameras 1 and 2 to determine if the calibration plate coincides with the light sheet.
References
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Journal ArticleDOI

Particle-Imaging Techniques for Experimental Fluid Mechanics

TL;DR: A review of these methods can be found in articles by Lauterborn & Vogel (1984), Adrian (1986a), Hesselink (1988), and Dudderar et al..
Journal ArticleDOI

Particle tracking velocimetry in three-dimensional flows

TL;DR: Hardware components for 3D PTV systems will be discussed, and a strict mathematical model of photogrammetric 3D coordinate determination, taking into account the different refractive indices in the optical path, will be presented.
Journal ArticleDOI

Stereoscopic particle image velocimetry applied to liquid flows

TL;DR: In this article, a twin-camera stereoscopic system was developed to extend conventional high image-density Particle Image Velocimetry (PIV) to three-dimensional vectors on planar domains.
Journal ArticleDOI

Scheimpflug stereocamera for particle image velocimetry in liquid flows.

TL;DR: A novel stereocamera has been developed based on the angular-displacement method, wherein the two camera axes are oriented in a nonorthogonal manner toward the object plane, which significantly reduces the radial distortions that arise when imaging through a thick liquid layer.
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