不同全景上异常检测的不相容模型

O. P. Arkhipov, M. Tsukanov
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引用次数: 1

摘要

开发无人机在同一区域内不同时刻的全景图自动比对方法是当前迫切需要解决的课题。在此基础上,提出了一种新的多时间全景图异常检测算法模型,通过对发现的奇异点和描述符进行比较,建立它们在全景图上的相互对应关系,并突出发现的异常非重叠区域的差异。提出了一种策略,旨在将全景图集中到一个视图中,并在随后进行同步。最后以所选被检测区域的多时间全景图为例,给出了算法的结果。我们设法在不同时间同步全景图,以尽量减少拍摄角度和照明的差异。对多时间全景图进行异常搜索,排除“噪声”类异常和特殊点颜色、几何坐标偏差较小的异常选择。将发现的异常按重要性分组排序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Incompatimic model of anomaly detection on different panoramas
The development of automatic methods for comparing panoramas obtained at different times during the inspection flight of UAVs of the same area is currently an urgent and popular task. In this connection, a new algorithmic model for detecting anomalies on multi-time panoramas was proposed, based on the comparison of the found singular points and descriptors, establishing their mutual correspondence on panoramas, and highlighting the found differences in non-overlapping areas of anomalies. The strategy aimed at bringing the panoramas to a single view and their subsequent synchronization is proposed. The results of the algorithm are presented, using the example of multi-time panoramas of the selected inspected area. We managed to synchronize the panoramas at different times to minimize differences in the shooting angles and illumination. Perform a search for anomalies on multi-time panoramas, excluding the selection of anomalies of the "noise" type and minor deviations in the color and geometric coordinates of special points. Sort the found anomalies by importance groups.
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