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Adaptive Multi-image Direct Georeferencing for Unmanned Aerial Vehicle Application

机译:无人驾驶飞行器应用的自适应多图像直接地理

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Due to the flexibility and unmanned property, unmanned aerial vehicle (UAV) has been used on a wide range of applications and conditions recently. In the large number of possible applications, real time and accurate georeferencing is very important. Direct georeferencing with out ground control points is defined as the direct measurement of the imaging sensor external orientation parameters (EOP) using positioning and orientation sensors, which is a popular research area. This paper proposes a new adaptive multi-image direct georeferencing for UAV applications. Based on bundle block adjustment, the proposed method designs an adaptive initialization strategy for different image data and application scenes. Due to the error cancellation property of multi directional images, it improves the localization accuracy. The experiments show exciting results.
机译:由于灵活性和无人性,无人驾驶车辆(UAV)最近已用于广泛的应用和条件。在大量可能的应用程序中,实时和准确的地理传播非常重要。具有外地控制点的直接地理转移被定义为使用定位和方向传感器的成像传感器外向参数(EOP)的直接测量,这是一个流行的研究区域。本文提出了一种用于UAV应用的新的自适应多图像直接地理学。基于束块调整,所提出的方法为不同的图像数据和应用场景设计了自适应初始化策略。由于多向图像的错误取消属性,它提高了本地化精度。实验表明了令人兴奋的结果。

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