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Method and system for visual change detection using multi-scale analysis

机译:利用多尺度分析进行视觉变化检测的方法和系统

摘要

The disclosure herein generally relate to scene change detection, and, more particularly, to use of Unmanned Vehicle (UV) to inspect a scene and perform a scene change detection using UVs. When a UV performs visual inspection of an area or an object, due to various factors, such as but not limited to environmental factors, and movement of object and/or the UV, image of the area/object captured by the drone lacks clarity, which in turn makes detection of any object a difficult task. The UV disclosed herein uses a multi scale super pixel technique for visual change detection, in order to solve the aforementioned issues. In an embodiment, the UV captures an image, identifies a reference image that matches the captured image, and generates a change map. The multi-scale super pixel analysis is then performed on this change map to detect changes between the captured image and the reference image.
机译:本文中的公开总体上涉及场景改变检测,并且更具体地,涉及无人驾驶车辆(UV)的使用以检查场景并使用UV执行场景改变检测。当UV对某个区域或物体进行视觉检查时,由于各种因素(例如但不限于环境因素)以及物体和/或UV的移动,无人机所捕获的区域/物体的图像会变得不清晰,反过来,这使检测任何物体变得困难。为了解决上述问题,本文公开的UV使用多尺度超像素技术进行视觉变化检测。在一个实施例中,UV捕获图像,识别与捕获的图像匹配的参考图像,并生成变化图。然后,对该变化图执行多尺度超像素分析,以检测捕获图像和参考图像之间的变化。

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