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Dynamic background subtraction based on appearance and motion pattern

机译:基于外观和运动模式的动态背景扣除

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Moving objects detection plays a critical role in computer vision application, since it usually is the first phase in video processing. Most traditional methods are used in static scenes, however not perform well in dynamic situations, or they can only overcome limited perturbation. In this paper, we propose a stereo local binary pattern based on appearance and motion (SLBP-AM) descriptor for back-ground modeling and objects detection. We regard the motion of pixels as dynamic texture in ellipsoidal domain, and combine texture histograms in the XY, XT, YT planes in the ellipsoid as the new descriptor for background subtraction. Compared with traditional local binary pattern (LBP) descriptor, experiment results show that the new proposed method can not only be robust to slight disturbance, but also adapt quickly to the large-scale and sudden changes.
机译:运动对象检测在计算机视觉应用中起着至关重要的作用,因为它通常是视频处理的第一阶段。大多数传统方法都用于静态场景,但是在动态情况下效果不佳,或者只能克服有限的干扰。在本文中,我们提出了一种基于外观和运动的立体局部二进制模式(SLBP-AM)描述符,用于背景建模和对象检测。我们将像素的运动视为椭圆域中的动态纹理,并将椭圆形中XY,XT,YT平面中的纹理直方图组合为背景减除的新描述符。实验结果表明,与传统的局部二值模式描述器相比,该方法不仅具有鲁棒性,对轻度扰动具有鲁棒性,而且能够快速适应大范围和突发性变化。

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