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Raindrop Detection and Removal from Long Range Trajectories

机译:雨滴检测和远程航迹去除

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In rainy scenes, visibility can be degraded by raindrops which have adhered to the windscreen or camera lens. In order to resolve this degradation, we propose a method that automatically detects and removes adherent raindrops. The idea is to use long range trajectories to discover the motion and appearance features of raindrops locally along the trajectories. These motion and appearance features are obtained through our analysis of the trajectory behavior when encountering raindrops. These features are then transformed into a labeling problem, which the cost function can be optimized efficiently. Having detected raindrops, the removal is achieved by utilizing patches indicated, enabling the motion consistency to be preserved. Our trajectory based video completion method not only removes the raindrops but also complete the motion field, which benefits motion estimation algorithms to possibly work in rainy scenes. Experimental results on real videos show the effectiveness of the proposed method.
机译:在下雨的场景中,附着在挡风玻璃或相机镜头上的雨滴会降低能见度。为了解决这种降级问题,我们提出了一种自动检测并去除附着的雨滴的方法。这个想法是使用远距离轨迹来发现沿轨迹局部的雨滴的运动和外观特征。这些运动和外观特征是通过我们分析遇到雨滴时的轨迹行为获得的。然后将这些特征转化为标记问题,可以有效地优化成本函数。在检测到雨滴之后,可以通过使用所示的补丁来去除雨滴,从而保持运动的一致性。我们基于轨迹的视频完成方法不仅去除了雨滴,而且还完成了运动场,这有利于运动估计算法在雨天下工作。在真实视频上的实验结果表明了该方法的有效性。

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