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Optimized dynamic background subtraction technique for moving object detection and tracking

机译:优化的动态背景扣除技术,用于运动物体的检测和跟踪

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摘要

Moving Object detection and tracking in a video have applications in video-surveillance and robotics, human-computer interaction. Three frame differencing is better than two frames difference technique due to fewer problems of holes. Dynamic background detection technique is much better than static background technique for video with background change. So in this paper, background is updated with averaging of frame t-1, frame t+1 and previous updated background. This updated background is subtracted from frame t for foreground detection and merged with three frame subtraction. 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 work, the proposed technique is able to reduce the holes problem in dynamic background updating video. This technique is extract foreground better than existing static and dynamic background.
机译:视频中的运动对象检测和跟踪在视频监视和机器人技术,人机交互中具有应用。由于较少的孔洞问题,三帧差分优于两帧差分技术。对于具有背景变化的视频,动态背景检测技术比静态背景技术要好得多。因此,在本文中,通过对帧t-1,帧t + 1和先前更新的背景进行平均来更新背景。从帧t中减去此更新的背景以进行前景检测,并与三帧减法合并。因此,有一个工作范围,即应进一步减少孔洞问题,并应在背景动态变化中更好地检测物体。在这项工作中,所提出的技术能够减少动态背景更新视频中的孔洞问题。该技术比现有的静态和动态背景更好地提取前景。

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