This paper demonstrates particle tracking velocimetry performed for a model system wherein particle-laden liquid metal flow around 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 for the wake flow around 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. Satisfactory tracking accuracy can be inferred from the fact that the fluctuations in the measured particle velocity are dominated by frequencies that agree sufficiently well with the expected frequencies of the cylinder wake. Graphical abstract: [Figure not available: see fulltext.].