Flying Objects Detection from a Single Moving Camera

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 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.


Published in:
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 4128-4136
Presented at:
Conference on Computer Vision and Pattern Recognition (CVPR), Boston, Massachusetts, USA, June 7-12, 2015
Year:
2015
ISBN:
978-1-4673-6964-0
Keywords:
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 Record created 2015-03-16, last modified 2018-09-13

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