  This paper demonstrates particle tracking velocimetry performed for a model
system wherein particle-laden liquid metal flow about a cylindrical obstacle
was studied. We present the image processing methodology developed for particle
detection in images with disparate and often low signal- and contrast-to-noise
ratios, and the application of our MHT-X tracing algorithm for particle
trajectory reconstruction within and about the wake flow of the obstacle.
Preliminary results indicate that the utilized methods enable consistent
particle detection and recovery of long, representative particle trajectories
with high confidence. However, we also underline the necessity of implementing
a more advanced particle position extrapolation approach for increased tracking
accuracy. We also show that the utilized particles exhibit the Stokes number
range that suggests good flow tracking accuracy, and that the particle time
scales extracted from reconstructed trajectories are consistent with
expectations based a priori estimates.
