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Optimized dynamic background subtraction technique for moving object detection and tracking

机译:用于移动物体检测和跟踪的优化动态背景减法技术

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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:在视频中移动对象检测和跟踪在视频监控和机器人中具有应用程序,人机交互。由于孔的问题较少,三帧差异优于两个帧差异技术。动态背景检测技术比静态背景技术更好,用于视频变化。因此,在本文中,使用帧T-1,帧T + 1和以前更新的背景的平均更新了背景。从FRAME T中减去该更新的背景,以进行前景检测,并与三个帧减法合并。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问题。这种技术比现有的静态和动态背景更好地提取前景。

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