A high performance architecture for object detection in drones
Ioannis Galanakis, Athanasios Milidonis, Ioannis Voyiatzis · 2021
Nowadays the use of drones in daily life is becoming more and more frequent. One important service of drones is object detection which is used in surveillance and search-and-rescue missions. High performance is a critical requirement for object detection, since drones travel at high flying speeds. Current systems mainly use software platforms which have limited performance. In this paper a hardware architecture is presented for object detection in drones. The ability of the proposed architecture to exploit parallelization in object detection tasks more efficiently than in software platforms, offers lower execution time and more accurate and faster results. The proposed architecture is implemented using an FPGA platform. Experimental results show the benefits of this architecture compared to a software platform in terms of performance and detection-precision.