The estimation of geolocation for aerial images is significant for tasks like map creating, or automatic navigation for unmanned aerial vehicles (UAVs). We propose a novel geolocalization method for the UAVs using only aerial images and reference road map. The corresponding road maps of the aerial images are firstly merged into a whole mosaic image using our newly-designed aerial image mosaicking algorithm, where the relative homography transformations between road images are firstly estimated using keypoints tracking in RGB aerial images, and then further refined with registration between detected roads. The geolocalization of the aerial mosaic image is then taken as the problem of registering observed roads in the aerial images to the reference road map under the homography transformation. The registration problem is solved with our fast search algorithm based on a novel projective-invariant feature, which consists of two road intersections augmented with their tangents. Experiments demonstrate that the proposed method can localize the aerial image sequence over an area larger than 1000 km\(^2\) within a few seconds.

中文翻译：

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无人机航拍序列的地理定位

航空图像的地理位置估计对于诸如地图创建或无人机的自动导航等任务非常重要。我们仅使用航拍图像和参考路线图为无人机提出一种新颖的地理定位方法。首先使用我们新设计的航拍图像镶嵌算法将航拍图像的对应路线图合并为整个镶嵌图像，其中首先使用RGB航拍图像中的关键点跟踪来估算道路图像之间的相对单应性变换，然后通过在检测到的道路之间进行配准。然后，将航空马赛克图像的地理定位作为在单应性变换下将航空图像中观察到的道路注册到参考道路地图的问题。通过基于新的射影不变特征的快速搜索算法解决了配准问题，该算法由两个道路交叉点的切线扩展而成。实验表明，该方法可以将航拍图像序列定位在大于1000 km的区域\（^ 2 \）在几秒钟内。