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A novel algorithm of adaptive background estimation

机译:一种新的自适应背景估计算法

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We propose an adaptive background estimation algorithm for an outdoor video surveillance system. In order to enhance the ability of adaptation to illumination changes and variant noise in long-term running, an improved Kalman filtering model based on the local-region is discussed to dynamically estimate a background image, in which the parameters are predicted by a recursive-least-square adaptive filter. The experimental results on real-world video show that the algorithm can perform robustly and effectively.
机译:我们提出了一种用于户外视频监控系统的自适应背景估计算法。为了增强长期运行中对光照变化和变化噪声的适应能力,讨论了一种基于局部区域的改进卡尔曼滤波模型来动态估计背景图像,其中参数通过递归算法进行预测。最小二乘自适应滤波器。在真实视频上的实验结果表明,该算法可以鲁棒有效地执行。

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