Experimental research into severe nuclear accidents may entail the discharge of a very high-temperature lava-like molten fuel mixture, corium, either into a pool of less-dense, more-volatile coolant or onto a solid substrate where the corium will spread and cool. In both instances, remote, high-speed video imaging is usually required to interpret these transient interactions and PTV represents a powerful tool for the characterisation of the dynamic properties of discrete melt fragments or distinctive features in the surface of the melt during spreading. Nuclear fuel-coolant interactions present particular challenges for PTV analysis as a molten jet and its fragments can exhibit high rates of inter-frame deformation and undergo fragmentation with a relatively high frequency. A PTV algorithm, adapted to these challenges, is presented whereby a user-defined tolerance in the evolution of certain particle properties is used to refine the potential candidate particles prior to particle matching. This candidate refinement step is used to distinguish between acceptable levels of deformation between successive sightings of a given particle, and more substantial changes consistent with fragmentation or coalescence, requiring the tracking of a new particle. Implementation of the PTV algorithm is presented for (1) an X-ray video from the FCINA-30-1 experiment between a jet of molten stainless steel and liquid sodium, conducted at the JAEA’s MELT facility, and (2) video imaging of the VE-U9-ceramic experiment of a molten corium-thermite mixture spreading on a zirconium substrate, conducted at the CEA’s VULCANO facility. The latter case-study enabled the characterization of > 70,000 local velocity vectors at locations corresponding to distinctive temperature heterogeneities in the surface of the spreading melt, providing extensive insight into the spreading dynamics for the validation of corium spreading models.