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INTEGRATION OF A GENERALISED BUILDING MODEL INTO THE POSE ESTIMATION OF UAS IMAGES

机译:将广义建筑模型集成到UAS图像的姿势估计中

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A hybrid bundle adjustment is presented that allows for the integration of a generalised building model into the pose estimation of image sequences. These images are captured by an Unmanned Aerial System (UAS) equipped with a camera flying in between the buildings. The relation between the building model and the images is described by distances between the object coordinates of the tie points and building model planes. Relations are found by a simple 3D distance criterion and are modelled as fictitious observations in a Gauss-Markov adjustment. The coordinates of model vertices are part of the adjustment as directly observed unknowns which allows for changes in the model. Results of first experiments using a synthetic and a real image sequence demonstrate improvements of the image orientation in comparison to an adjustment without the building model, but also reveal limitations of the current state of the method.
机译:提出了一种混合束调整,其允许将广义的建筑模型集成到图像序列的姿势估计中。这些图像由装备的无人机系统(UAS)捕获,在建筑物之间飞行。建筑模型与图像之间的关系由连接点和建筑模型平面的物体坐标之间的距离描述。通过简单的3D距离标准发现关系,并在高斯 - 马尔可夫调整中被建模为虚拟观察。模型顶点的坐标是调整的一部分,直接观察到的未知数,允许模型的变化。使用合成和实图像序列的第一实验结果表明,与没有建筑模型的调整相比,展示了图像取向的改进,而且还揭示了该方法的当前状态的限制。

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