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Hybrid object detection using improved three frame differencing and background subtraction

机译:使用改进的三帧差异和背景减法的混合对象检测

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Object Detection and Tracking in video has applied in robotics, video-surveillance; human-computer interaction etc. and different approach of object detection e.g. Background subtraction, frame differencing. Motion based recognition is one of the methods to detect objects in sequence of image. In this method, a video sequence containing a large number of images is used to extract motion information. Two frame differencing is very easy but there is problem of holes. Three frame differencing and background subtraction have solved the problem of holes of two frames till a limit. Background subtraction is used for stable background video but Dynamic Background subtraction is capable to detect object in video with gradual background changes. So there is scope of work such that holes problem should be reduced more and object should be detected better in dynamic changes in background. In this paper, the proposed technique is able to reduce the holes problem in dynamic background updating video.
机译:视频中的对象检测和跟踪应用于机器人,视频监控;人计算机相互作用等和物体检测的不同方法。背景减法,帧差异。基于运动的识别是以图像序列检测对象的方法之一。在该方法中,使用包含大量图像的视频序列来提取运动信息。两个帧差异非常容易,但存在孔的问题。三个帧差异和背景减法已经解决了两个框架的孔,直到极限。背景下减法用于稳定背景视频,但动态背景减法能够在视频中检测对象,逐渐变化。因此,工作范围是工作范围,即应该减少孔问题,并且在背景中的动态变化中应该更好地检测到对象。在本文中,所提出的技术能够减少动态背景更新视频中的孔问题。

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