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Moving targets detection from UAV based on a robust real-time image registration algorithm

机译:基于坚固的实时图像配准算法,从UV移动目标检测

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In this paper, a real time method for image registration dedicated to small moving target detection (MTD) from a moving camera is proposed. The main application is the road surveillance from UAV. The algorithm must work under strong constraints: real time performances for VGA images at 30 fps with a standard PC and shaking camera with irregular movements. Given the medium-altitude of the UAV, the estimated transformation is a similarity. Our proposed algorithm is an hybrid method using an ESM algorithm (Efficient Second-Order Minimization) and Harris corners matching, with pyramidal implementation. An M-Estimator is used at each loop of the ESM in order to be robust to moving objects, occlusions and camera noise. We have tested our method on UAV highway images and this coupling allows for robustness, low time computation and accuracy. Even if the camera may have important oscillations, we get a high precision alignment of the images and thus a reliable detection of the moving targets.
机译:在本文中,提出了一种用于从移动相机的小于移动目标检测(MTD)的图像登记的实时方法。 主要应用是无人机的道路监控。 该算法必须在强制限制下工作:具有30 FPS的VGA图像的实时性能,具有标准PC和具有不规则运动的振动相机。 鉴于UAV的中高度,估计的变换是一种相似性。 我们所提出的算法是一种混合方法,使用了符合金字塔的实现的ESM算法(有效的二阶最小化)和哈里斯角匹配。 在ESM的每个循环中使用M估算器,以便对移动物体,闭塞和相机噪声具有鲁棒。 我们在UAV公路图像上测试了我们的方法,这种耦合允许鲁棒性,低时间计算和准确性。 即使相机可能具有重要的振荡,我们也可以获得图像的高精度对准,从而可靠地检测移动目标。

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