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A novel method performing 3D PTV from double frame multi-camera images is introduced. Particle velocities are estimated by following three steps. Firstly, separate particle reconstructions with a sparsity-based algorithm are performed on a…

Particle tracking velocimetry in 3D is becoming an increasingly important imaging tool in the study of fluid dynamics, combustion as well as plasmas. We introduce a dynamic discrete tomography algorithm for reconstructing particle…

Fluid Dynamics · Physics 2015-01-23 Andreas Alpers , Peter Gritzmann , Dmitry Moseev , Mirko Salewski

We introduce the first comprehensive approach to determine the uncertainty in volumetric Particle Tracking Velocimetry (PTV) measurements. Volumetric PTV is a state-of-the-art non-invasive flow measurement technique, which measures the…

Fluid Dynamics · Physics 2022-10-19 Sayantan Bhattacharya , Pavlos P. Vlachos

3D particle tracking velocimetry (PTV) is a key technique for analyzing turbulent flow, one of the most challenging computational problems of our century. At the core of 3D PTV is the dual-frame fluid motion estimation algorithm, which…

Computer Vision and Pattern Recognition · Computer Science 2024-10-17 Yifei Zhang , Huan-ang Gao , Zhou Jiang , Hao Zhao

Resuspension of solid particles by a tornado-like vortex from surfaces of different roughness is studied using a three-dimensional particle tracking velocimetry (3D-PTV) method. By utilizing the three-dimensional information on particle…

Fluid Dynamics · Physics 2015-09-29 Ron Shnapp , Alex Liberzon

Flow visualization technologies such as particle tracking velocimetry (PTV) are broadly used in understanding the all-pervasiveness three-dimensional (3D) turbulent flow from nature and industrial processes. Despite the advances in 3D…

Fluid Dynamics · Physics 2022-11-01 Jiaming Liang , Chao Xu , Shengze Cai

Particle Imaging Velocimetry (PIV) estimates the flow of fluid by analyzing the motion of injected particles. The problem is challenging as the particles lie at different depths but have similar appearance and tracking a large number of…

Computer Vision and Pattern Recognition · Computer Science 2020-03-24 Zhong Li , Jinwei Ye , Yu Ji , Hao Sheng , Jingyi Yu

Direct estimation of Lagrangian turbulence statistics is essential for the proper modeling of dispersion and transport in highly obstructed canopy flows. However, Lagrangian flow measurements demand very high rates of data acquisition,…

Fluid Dynamics · Physics 2019-05-16 Ron Shnapp , Erez Shapira , David Peri , Yardena Bohbot-Raviv , Eyal Fattal , Alex Liberzon

Particle tracking velocimetry (PTV) is widely used to measure time-resolved, three-dimensional velocity and pressure fields in fluid dynamics research. Inaccurate localization and tracking of particles is a key source of error in PTV,…

Fluid Dynamics · Physics 2026-03-31 Ke Zhou , Jiaqi Li , Jiarong Hong , Samuel J. Grauer

A particle tracking velocimetry apparatus is presented that is capable of measuring three-dimensional particle trajectories across large volumes, of the order of several meters, during natural snowfall events. Field experiments, aimed at…

Fluid Dynamics · Physics 2023-04-12 Nathaniel Bristow , Jiaqi Li , Peter Hartford , Michele Guala , Jiarong Hong

The collective behavior of levitated particles in a weakly-ionized plasma (dusty plasma) has raised significant scientific interest. This is due to the complex array of forces acting on the particles, and their potential to act as in-situ…

Plasma Physics · Physics 2023-06-28 Wentao Yu , Justin C. Burton

The continual increase in computational power and the improvement of algorithms for particle tracking in the past decade have been making it feasible to track larger amounts of particles in 3D Volumetric Particle Tracking Velocimetry…

Optics · Physics 2025-02-11 H. Abitan , Y. Zhang , S. l. Ribergård , C. M. Velte

Particle Image Velocimetry (PIV) estimates velocities through correlations of particle images within interrogation windows, leading to a spatial modulation of the velocity field. Although in principle Particle Tracking Velocimetry (PTV)…

Fluid Dynamics · Physics 2023-02-14 Iacopo Tirelli , Andrea Ianiro , Stefano Discetti

In the past decades, great progress has been made in the field of optical and particle-based measurement techniques for experimental analysis of fluid flows. Particle Image Velocimetry (PIV) technique is widely used to identify flow…

Image and Video Processing · Electrical Eng. & Systems 2021-01-29 Nikolay Stulov , Michael Chertkov

Three-dimensional particle reconstruction with limited two-dimensional projections is an under-determined inverse problem that the exact solution is often difficult to be obtained. In general, approximate solutions can be obtained by…

Image and Video Processing · Electrical Eng. & Systems 2021-09-14 Qi Gao , Shaowu Pan , Hongping Wang , Runjie Wei , Jinjun Wang

Two-dimensional Particle Tracking Velocimetry (PTV) is a promising technique to study the behaviour of granular flows. The aim is to experimentally determine the free surface width and position of the shear band from the velocity profile to…

The study of moving particles (e.g. molecules, virus, vesicles, organelles, or whole cells) is crucial to decipher a plethora of cellular mechanisms within physiological and pathological conditions. Powerful live-imaging approaches enable…

Numerical Analysis · Mathematics 2023-11-13 Eloina Corradi , Maurizio Tavelli , Marie-Laure Baudet , Walter Boscheri

3D Particle Imaging Velocimetry (3D-PIV) aim to recover the flow field in a volume of fluid, which has been seeded with tracer particles and observed from multiple camera viewpoints. The first step of 3D-PIV is to reconstruct the 3D…

Computer Vision and Pattern Recognition · Computer Science 2018-05-23 Katrin Lasinger , Christoph Vogel , Thomas Pock , Konrad Schindler

An important tool for experimental fluids mechanics research is Particle Image Velocimetry (PIV). Several robust methodologies have been proposed to perform the estimation of velocity field from the images, however, alternative methods are…

Computer Vision and Pattern Recognition · Computer Science 2025-02-03 Efraín Magaña , Francisco Sahli Costabal , Wernher Brevis

In this paper, we present a comprehensive evaluation to establish a robust and efficient framework for Lagrangian-based particle tracing using deep neural networks (DNNs). Han et al. (2021) first proposed a DNN-based approach to learn…

Graphics · Computer Science 2024-05-16 Mengjiao Han , Jixian Li , Sudhanshu Sane , Shubham Gupta , Bei Wang , Steve Petruzza , Chris R. Johnson
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