Over the past few decades, progress in animal tracking techniques, from large migrating mammals to swarming insects, has facilitated significant advances in ecology, behavioural biology, and conservation science. Recently, we developed a technique to record and track flashing fireflies in their natural habitat using pairs of 360-degree cameras. The method, which has the potential to help identify and monitor firefly populations worldwide, was successfully implemented in various natural swarms. However, camera calibration remained tedious and time-consuming. Here, we propose and implement an algorithm that calibrates the cameras directly from the data, requiring minimal user input. We explain the principles of the calibration-free algorithm, and demonstrate the ease and efficiency of its implementation. This method is relatively inexpensive, versatile, and well-suited for automatic processing and the collection of a large dataset of firefly trajectories across species and populations. This calibration-free method paves the way to citizen science efforts for monitoring and conservation of firefly populations.