Datasets for "STELLA - a modular framework for StatioTemporal Event-based Lagrangian particLe trAcking"

We introduce STELLA (v1.0.2), a modular framework for statiotemporal event-based Lagrangian particle tracking in fluid flows. The framework is implemented as a GUI in python and takes the raw event stream obtained from an event-based camera as input. Once the data is loaded, the processing is done in four steps: Preprocessing, Detection, Tracking, Validation. In preprocessing, a ROI can be set in time and space and the filtered events can be saved. Subsequently, different algorithms for direct processing and image-based detection can be used to identify clustered events associated to individual particles. Based on the clustered events, particle tracks (position, velocity) can be derived by using a Kalman filter, spline fitting or hybrid approaches. Finally, a track quality filter and a neighborhood filter can be applied to reject spurious tracks during validation. In every step, the evaluation results can be saved and loaded in a way that also just single modules of STELLA can be used. For further information, please find our paper here: STELLA: a modular framework for SpatioTemporal Event-based Lagrangian particLe trAcking | Experiments in Fluids | Springer Nature Link