Uncertainty Estimation Methods in Particle Image Velocimetry

Quantification of uncertainty in a stereoscopic particle image velocimetry measurement

In Stereoscopic Particle Image Velocimetry (Stereo-PIV), the three velocity components are obtained by illuminating a planar region in the fl ow fi eld and recording the region of interest using two cameras at an angle. Calibration, planar velocity estimation, and velocity reconstruction are the three essential steps involved in the process. Earlier efforts to quantify the accuracy in a Stereo-...

Variational Optical Flow Estimation for Particle Image Velocimetry

We introduce a novel class of algorithms for evaluating PIV image pairs. The mathematical basis is a continuous variational formulation for globally estimating the optical flow vector fields over the whole image. This class of approaches has been known in the field of image processing and computer vision for more than two decades but apparently has not been applied to PIV image pairs so far. We...

Holography and particle image velocimetry

The contribution of holographic techniques to particle velocity measurements is discussed. Two-dimensional holographic particle image velocimetry and three-dimensional holographic velocimetry are described and compared. Their advantages and limits are discussed and the latest progress in this domain is presented, together with perspectives for the near future.

Recent Advances in Micro-Particle Image Velocimetry

Microfluidic devices are becoming increasingly common and are seen in applications ranging from biology to nanotechnology and manufacturing. Flow behavior in these small domains can often be counterintuitive because of the low Reynolds number or the relative importance of surface forces. Microparticle image velocimetry (μPIV) is a quantitative method that can be used to characterize the perform...

Particle Image Velocimetry Correlation Signal-to-noise Metrics, Particle Image Pattern Mutual Information and Measurement uncertainty Quantification