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Mesh-based global motion compensation for robust mosaicking and detection of moving objects in aerial surveillance

机译:基于网格的全球运动补偿,用于稳健的摩托车和检测空中监测中的移动物体

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Global Motion Compensation is one of the key technologies for aerial image processing e.g. to detect moving objects on the ground or to generate a mosaick image of the observed area. For this task, it is necessary to estimate and compensate the motion of the pixels between the recorded frames evoked by the movement of the camera. As the camera is statically attached to a flying device such as a quadro-copter (also called Micro Air Vehicle, MAV) or a helicopter, the motion of the camera directly corresponds to the plane movements. For simplification, only a planar landscape model is used nowadays to describe the global motion of the scene. However, if objects like buildings or mountains are close to the camera, i.e. the MAV is at a low altitude, this simplification is not valid. Therefore we propose a more complex model by introducing a 2D mesh-based motion compensation technique, also known as image warping, to compensate the global motion. We show the benefits if used for mosaick creation by smaller artifacts due to perspective distortions and smaller drift problems. We also improve a moving object detection system to identify moving objects more reliably. Moreover, the proposed method is also more robust in case of lens distortions.
机译:全球运动补偿是空中图像处理的关键技术之一。检测地面上的移动物体或生成观察区域的MOSAICK图像。对于此任务,有必要估计和补偿由相机移动所引起的记录帧之间的像素之间的运动。当相机静态附接到诸如Quadro-Copter(也称为微空气车辆,MAV)或直升机的飞行装置上时,相机的运动直接对应于平面运动。为了简化,目前仅使用平面景观模型来描述场景的全局运动。但是,如果像建筑物或山脉这样的物体接近相机,即,MAV处于低空,这种简化无效。因此,我们通过引入基于2D网格的运动补偿技术来提出更复杂的模型,也称为图像翘曲,以补偿全局运动。如果由于透视扭曲和较小的漂移问题,我们展示了较小的伪像的摩西克创作的好处。我们还改善了移动的物体检测系统,以更可靠地识别移动物体。此外,在镜片扭曲的情况下,该方法也在更加稳健。

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