2000
DOI: 10.2514/3.14437
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Application of neural networks to stereoscopic imaging velocimetry

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Cited by 5 publications
(9 citation statements)
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“…For particle tracking, which is the most important and challenging step in STV, the Hopfield neural network was employed to find appropriate particle tracks, owing to its excellent capability in solving global optimization problems. The previous investigation by Ge and Cha [10,11] indicates that neural network can be robust and efficient for particle tracking.…”
Section: Description Of Stv and Results Of Particle Tracking Algorithmsmentioning
confidence: 97%
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“…For particle tracking, which is the most important and challenging step in STV, the Hopfield neural network was employed to find appropriate particle tracks, owing to its excellent capability in solving global optimization problems. The previous investigation by Ge and Cha [10,11] indicates that neural network can be robust and efficient for particle tracking.…”
Section: Description Of Stv and Results Of Particle Tracking Algorithmsmentioning
confidence: 97%
“…The data acquisition and processing steps of STV are shown in Fig. 1 and the details of the methodology have been previously presented by Ge and Cha [10]. Camera calibration is the step for finding the relationship between CCD image positions to corresponding rays in space.…”
Section: Description Of Stv and Results Of Particle Tracking Algorithmsmentioning
confidence: 99%
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“…This tracking on the 3D coordinates has been also applied by other authors (e.g., [17,29,35,38,39]). An alternative strategy consists in first building the trajectories in each of the 2D image spaces, and then to find the 3D correspondence between them [11][12][13]34]. It has been shown for instance in [37] that the former strategy is more efficient in principle and it will therefore be retained for the present project.…”
Section: Introductionmentioning
confidence: 99%
“…Particle tracking schemes can be divided into three main categories: -Image plane based tracking schemes: Particles are tracked on each camera 2D image plane separately through time (temporal tracking). Afterwards, the resulting 2D trajectories are matched in 3D object space and the 3D coordinates are calculated (Biwole et al, 2009;Engelmann, 1998Engelmann, , 2000Ge & Cha, 2000;Guenzennec et al, 1994;Jähne, 1997;Li et al 2008;Wierzimok & Hering, 1993) -Object plan based tracking schemes: Particle 3D coordinates are first calculated at each time step separately. Afterwards, the resulting set of time-ordered 3D coordinates is the only input for temporal tracking directly in object space.…”
Section: Particle Trackingmentioning
confidence: 99%