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Improved Object Geo-Location in Airborne Camera Images using Tight Integration of Vision and Navigation Data

机译:通过紧密集成视觉和导航数据,改善了机载相机图像中的对象地理位置

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摘要

A method for precise geo-location of objects that are observed by an airborne camera is described in this paper. The platform for image acquisition is a micro aerial vehicle (MAV) with an integrated navigation system. From the captured image sequences and MAV navigation data, the three-dimensional positions of objects of interest are retrieved. Different techniques for image feature tracking are compared. Combining measurements from multiple viewpoints in a Bundle Adjustment process yields optimal accuracy of the estimated object positions. The robustness of the optimization is enhanced by tight integration of data from both the vision and the navigation system.
机译:本文介绍了一种通过航空相机观察物体的精确地理位置的方法。图像采集平台是带有集成导航系统的微型飞行器(MAV)。从捕获的图像序列和MAV导航数据中,检索出感兴趣对象的三维位置。比较了用于图像特征跟踪的不同技术。在“束调整”过程中组合来自多个视点的测量结果可得出估计的物体位置的最佳精度。通过视觉和导航系统数据的紧密集成,可以增强优化的鲁棒性。

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