Name
Abstract | ||
|---|---|---|
Digital particle image velocimetry (DPIV) aims at flow visualisation and measurement of flow dynamics in numerous applications. The fluid is seeded with particles that follow the flow and efficiently scattered light. Traditionally, FFT-based correlation techniques were used to estimate the displacements of the particles in a digital PIV sequence. Recently, an optical flow estimation technique developed in computer vision has been successfully applied to DPIV. In this paper we study the DPIV-efficiency of another group of tracking approaches, the feature tracking techniques. Velocity fields obtained by several methods are compared for synthetic and real PIV sequences. It is concluded that feature tracking algorithms applied to DPIV are a useful alternative to both the correlation and the optical flow algorithms |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1109/ICPR.2000.902995 | ICPR |
Keywords | Field | DocType |
digital particle image,digital instrumentation,optical flow estimation technique,digital particle image velocimetry,optical flow algorithm,real piv sequence,feature tracking,flow visualization,motion estimation,optical tracking,combustion process,tracking techniques applied,digital piv sequence,digital piv,hydrodynamics,computer vision,flow visualisation,flow dynamic,aeronautical phenomenon,flow dynamics,flow measurement,fft-based correlation technique,velocity field,testing,optical pumping,visualization,optical scattering,optical flow,aerodynamics | Particle tracking velocimetry,Computer vision,Particle image velocimetry,Computer science,Flow measurement,Fast Fourier transform,Digital image correlation,Artificial intelligence,Motion estimation,Flow visualization,Optical flow | Conference |
Volume | ISSN | ISBN |
4 | 1051-4651 | 0-7695-0750-6 |
Citations | PageRank | References |
2 | 0.47 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chetverikov, D. | 1 | 956 | 99.89 |
| Nagy, M. | 2 | 2 | 0.47 |
| Verestoy, J. | 3 | 2 | 0.47 |