Abstract

<p indent="0mm">For real-time shooting of complex dynamic scenes, people still rely on controlling manually now. For automatically and completely shooting this kind of scene, a feasible solution is proposed, which divides the problem into 3 sub problems: scene segmentation, photography composition, and UAV (unmanned aerial vehicle) scheduling. First, on scene segmentation, <italic>K</italic>-means clustering is utilized with threshold to get a series of small segmented scenes. Each small scene is corresponded by a single UAV. Then, according to the location of these small scenes, the best shooting positions of UAVs are calculated, which ensure that each small scene is shot completely and meanwhile the pictures shot by different UAVs are relevant and holistic. Finally, in order to minimize the total flight distance and flight cost of the UAV group, the UAV flight scheduling problem is turned into a task assignment problem, where Hungarian algorithm is applied to determine the final shooting positions for each UAV to complete its corresponding shooting task. By this way, a complex dynamic scene can be continuously shot in real-time. Experiments in simulation program shows that the algorithm can provide effective control on multiple UAVs to continuously and automatically shoot a complex dynamic scene, including all the objects inside the scene from multi-view in real-time. By observing trajectories of UAVs and objects’ positions in shooting results, it is sure that proposed method produces results with much higher quality comparing with the naive method of average view division.

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