2022
DOI: 10.1016/j.softx.2022.101204
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SerialTrack: ScalE and rotation invariant augmented Lagrangian particle tracking

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Cited by 6 publications
(5 citation statements)
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“…Hence, testing on real-world datasets becomes essential for validation. To ascertain our method's efficacy in real-world PTV experiments, in this section, we test it with two real-world datasets, DeformationFlow [32] and Aortic Valve Interstitial Cell (AVIC) [33]. The models, trained on the FluidFlow3D-NORM dataset, are utilized for two distinct real-world PTV tasks: one in the physical domain and the other in the biological domain.…”
Section: Real Ptv Experimentsmentioning
confidence: 99%
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“…Hence, testing on real-world datasets becomes essential for validation. To ascertain our method's efficacy in real-world PTV experiments, in this section, we test it with two real-world datasets, DeformationFlow [32] and Aortic Valve Interstitial Cell (AVIC) [33]. The models, trained on the FluidFlow3D-NORM dataset, are utilized for two distinct real-world PTV tasks: one in the physical domain and the other in the biological domain.…”
Section: Real Ptv Experimentsmentioning
confidence: 99%
“…Therefore, we adopt the existing PTV algorithm as a framework and use our method as its initialisation. We employ SerialTrack [32] as the particle tracking framework for this experiment. The original version is denoted as SerialTrack, while its adaptation with our scene flow estimation framework is termed Ours+ST.…”
Section: Deformationflowmentioning
confidence: 99%
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“…Randomly sampled data poses a challenge to gradient estimation. Even though local least-squares fitting of displacement fields and interpolation from irregular data to a regular grid have been reported [ 45 , 56 ], performance of the methods under large gradients is unclear, and the related estimation errors have not been completely characterized.…”
Section: Introductionmentioning
confidence: 99%
“…In this manuscript, a full-field method for estimating the deformation gradient tensor is proposed, based on the non-gridded displacement data obtained from particle tracking in a manner similar to recent work [ 56 ]. At each particle location, the deformation gradient tensor is estimated from the displacement measurements of the given center particle and its k -nearest neighbors (see the inset of Fig.…”
Section: Introductionmentioning
confidence: 99%