Feature matching for UAV navigation in urban environments

J. Sasiadek, M. Walker, A. Krzyżak
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引用次数: 7

Abstract

This research was motivated by a need for accurate UAV navigation using camera(s) to augment inertial navigation unit data while flying over, or through an urban environment. The process of position determination using cameras follows a sequence of well defined steps. First features must be found in consecutive-in-time images and then matched across time. The underlying camera motion, as defined by camera rotation and translation, may then be calculated as a homography, for example. Accurate homography determination requires use of a set of at least 4 feature pairs that are not collinear and are accurately matched. In this paper it is shown that collinearity of features in urban images is quite likely to occur. Thus, collinear features must be removed. This paper reports an easy way to do so and examines, as well, the issue of accurate matching. Preliminary results are reported.
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城市环境下无人机导航特征匹配
这项研究的动机是需要精确的无人机导航,使用相机(s)来增加惯性导航单元数据,而飞行时,或通过城市环境。使用相机确定位置的过程遵循一系列明确的步骤。首先,必须在连续的时间图像中找到特征,然后在时间范围内进行匹配。例如,由摄像机旋转和平移定义的底层摄像机运动可以计算为单应性。准确的单应性确定需要使用至少4个不共线且准确匹配的特征对的集合。本文的研究表明,城市图像中特征的共线性很可能发生。因此,必须去除共线特征。本文报告了一种简便的方法,并探讨了准确匹配的问题。初步结果报告。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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