Flying Objects Detection From a Single Moving Camera

Artem Rozantsev, Vincent Lepetit, Pascal Fua; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, pp. 4128-4136

We propose an approach to detect flying objects such as UAVs and aircrafts when they occupy a small portion of the field of view, possibly moving against complex backgrounds, and are filmed by a camera that itself moves. Solving such a difficult problem requires combining both appearance and motion cues. To this end we propose a regression-based approach to motion stabilization of local image patches that allows us to achieve effective classifica- tion on spatio-temporal image cubes and outperform state- of-the-art techniques. As the problem is relatively new, we collected two chal- lenging datasets for UAVs and Aircrafts, which can be used as benchmarks for flying objects detection and vision- guided collision avoidance.