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A robust real-time image algorithm for moving target detection from unmanned aerial vehicles (UAV)

机译:用于从无人机(UAV)进行运动目标检测的鲁棒实时图像算法

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We propose a real time method for moving target detection from a camera embedded on a UAV. As the camera is moving, we must estimate the background motion in order to compensate it and then perform the moving target detection. This compensation is realized by an image registration method. For this, we use an hybrid method using global minimization and feature-based approaches, with a pyramidal implementation. The good results obtained for registration give us the potential moving targets. As some wrong detections still appear, due to noise, occlusions or local change of illuminations, we worked on a robust spatio-temporal tracker able to decide if potential targets are real moving targets or not. The algorithm must reach real time performances for VGA images at 30 fps with a standard PC.We have tested our method on different sequences and show the good results obtained thanks to the high precision in the image registration and the spatio-temporal tracker.
机译:我们提出了一种实时方法,用于从嵌入在无人机上的摄像机进行运动目标检测。当摄像机移动时,我们必须估计背景运动以对其进行补偿,然后执行运动目标检测。该补偿通过图像配准方法来实现。为此,我们使用混合方法,该方法使用全局最小化和基于特征的方法,并采用金字塔实现。注册获得的良好结果为我们提供了潜在的移动目标。由于仍然存在一些错误的检测结果,这是由于噪声,遮挡或照明的局部变化所致,因此我们开发了一款强大的时空跟踪器,能够确定潜在目标是否为真实的移动目标。该算法必须使用标准PC才能以30 fps的速度达到VGA图像的实时性能。我们已经在不同的序列上测试了我们的方法,并由于图像配准和时空跟踪器的高精度而显示出了良好的效果。

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