Abstract
Recent advances in unmanned aerial vehicle (UAV) technologies have made it possible to deploy an aerial video surveillance system to provide an unprecedented aerial perspective for ground monitoring in real time. Multiple UAVs would be required to cover a large target area, and it is difficult for users to visualize the overall situation if they were to receive multiple disjoint video streams. To address this problem, we designed and implemented SkyStitch, a multiple-UAV video surveillance system that provides a single and panoramic video stream to its users by stitching together multiple aerial video streams. SkyStitch addresses two key design challenges: (i) the high computational cost of stitching and (ii) the difficulty of ensuring good stitching quality under dynamic conditions. To improve the speed and quality of video stitching, we incorporate several practical techniques like distributed feature extraction to reduce workload at the ground station, the use of hints from the flight controller to improve stitching efficiency and a Kalman filter-based state estimation model to mitigate jerkiness. Our results show that SkyStitch can achieve a stitching rate that is 4 times faster than existing state-of-the-art methods and also improve perceptual stitching quality. We also show that SkyStitch can be easily implemented using commercial off-the-shelf hardware.
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