Rozantsev, ArtemLepetit, VincentFua, Pascal2015-03-162015-03-162015-03-16201510.1109/CVPR.2015.7299040https://infoscience.epfl.ch/handle/20.500.14299/112499We 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 classification on spatio-temporal image cubes and outperform state-of-the-art techniques. As the problem is relatively new, we collected two challenging datasets for UAVs and Aircrafts, which can be used as benchmarks for flying objects detection and vision-guided collision avoidance.object detectionspatio-temporal featuresmotion compensationtext::conference output::conference proceedings::conference paper