ROFD: Event-based 5k-fps Real-Time Optical Flow Detector for Transient Radiant Expanding Flares

Detecting transient radiant expanding flares is crucial for assessing the status of key devices like Hall thrusters, for which real-time detection is vital to maintain satellite stability in orbit. Event cameras are better suited for this task than high-speed cameras, offering faster perception speed, lower power consumption, and more compact sizes. While previous event-based works have significantly enhanced the visual processing speed, current approaches still fail to meet real-time requirements for transient flare detection, due to complex algorithms and inefficient hardware designs. To address the issues, we propose ROFD, an event-based 5k-fps real-time optical flow detector that includes: 1) A residual spatio-temporal-average optical flow detection algorithm that reduces the computing complexity and shortens the detection time window. 2) A tile-based interleaving memory mapping method that minimizes wasted memory access time. 3) Conflict-free data flows that eliminate data dependency and enhance parallelism. Experiments demonstrate that our FPGA-implemented ROFD operates at 5k-fps, achieving a maximum speedup of 35.4 × and a maximum accuracy improvement of 2.98×, while saving 87% DSPs, 33% BRAMs, and 58% power consumption compared to SOTA.