2001
DOI: 10.1006/rtim.1999.0203
|View full text |Cite
|
Sign up to set email alerts
|

A Vision-Based Particle Tracking Velocimetry

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2

Citation Types

0
2
0

Year Published

2002
2002
2023
2023

Publication Types

Select...
3
2
1

Relationship

0
6

Authors

Journals

citations
Cited by 8 publications
(2 citation statements)
references
References 23 publications
0
2
0
Order By: Relevance
“…In contrast, the PTV method belongs to the Lagrangian method [10], calculating the velocity by measuring the length of the particle optical trajectory under an exposure time interval. This method has strong real-time performance and the operation is simple [2], but the accuracy is relatively lower compared to the PIV algorithm. The LSV method is generally applied to dense granular flow.…”
Section: Introductionmentioning
confidence: 99%
“…In contrast, the PTV method belongs to the Lagrangian method [10], calculating the velocity by measuring the length of the particle optical trajectory under an exposure time interval. This method has strong real-time performance and the operation is simple [2], but the accuracy is relatively lower compared to the PIV algorithm. The LSV method is generally applied to dense granular flow.…”
Section: Introductionmentioning
confidence: 99%
“…Although recently new monitoring techniques like X-ray computer tomography (Coletta et al, 1991;Schreurs et al, 2003), particle image velocimetry (PIV, e.g. Baldassarre et al, 2001;Wolf et al, 2003;Hampel et al, 2004;Adam et al, 2005;Rosenau et al, 2009;Reiter et al, 2011), or laser scanning (e.g. Persson et al, 2004;Graveleau and Dominguez, 2008) have led to significant improvements in analysing and transfering sandbox experiments, the challenge to monitor 3-D evolution of structures within opaque bodies remains.…”
Section: Introductionmentioning
confidence: 99%