The purpose of cross-view image matching is to match images acquired from the different platforms of the same target scene and then help positioning system to infer the location of the target scene. With the rapid development of drone technology, how to help Drone positioning or navigation through cross-view matching technology has become a challenging research topic. However, the accuracy of current cross-view matching models is still low, mainly because the existing public datasets do not include the differences in images obtained by drones at different heights, and the types of scenes are relatively homogeneous, which makes the models unable to adapt to complex and changing scenes. We propose a new cross-view dataset, SUES-200, to address these issues.SUES-200 contains images acquired by the drone at four flight heights and the corresponding satellite view images under the same target scene. To our knowledge, SUES-200 is the first dataset that considers the differences generated by aerial photography of drones at different flight heights. In addition, we build a pipeline for efficient training testing and evaluation of cross-view matching models. Then, we comprehensively evaluate the performance of feature extractors with different CNN architectures on SUES-200 through an evaluation system for cross-view matching models and propose a robust baseline model. The experimental results show that SUES-200 can help the model learn features with high discrimination at different heights. Evaluating indicators of the matching system improves as the drone flight height gets higher because the drone camera pose and the surrounding environment have less influence on aerial photography.
翻译:交叉视图图像匹配的目的是匹配从同一目标场景的不同平台上获得的图像,然后帮助定位系统推断目标场景的位置。随着无人机技术的迅速发展,如何通过交叉视图匹配技术帮助无人机定位或导航已成为一个具有挑战性的研究课题。然而,当前交叉视图匹配模型的准确性仍然很低,主要是因为现有的公共数据集并不包括不同高度无人机获得的图像的差异,而且场景类型相对均匀,使得模型无法适应复杂和变化的场景。我们提议建立一个新的交叉视图数据集(SUES-200)来解决这些问题。SUES-200包含由无人机在四个飞行高度上和同一目标场景下相应的卫星视图图像所获取的图像。据我们所知,SUES-200是第一个考虑到不同飞行高度无人机空中摄影产生的差异的数据集。此外,我们为高效的培训测试和评估交叉视图匹配模型(SUES-200)的高级图像模型(SUES-200)的性能性能评估,因为SOS-200的飞行高度模型和高水平的模型(SUES-S-SU)的对比系统能够通过一个高的测试来对比高的测试。