基于卡尔曼滤波的自适应背景估计
首发时间:2010-03-24
摘要:卡尔曼滤波被广泛应用在图像序列的背景估计中,以实现从前景图像中分离出背景图像。本文将讨论一种自适应的背景估计方法,利用卡尔曼滤波因子选择抑制前景适应来排除突发滤波干扰,更加快速地适应背景图像序列中光照的变化,以及运动物体区域自适应。理论分析和实践证明,该算法在复杂光照环境下具有良好的适应性,实时性较好,运动目标检测的准确率也有明显提高。
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Adaptive Background Estimation using Kalman-Filtering
Abstract:In image sequence processing kalman filtering is used for an adaptive background estimation, in order to separate the foreground from the background. This paper will discuss an adaptive background estimation method, which using Kalman filtering factor for selective suppression of foreground adaptation in order to exclude the suddenly occurring interference, the presented algorithm can quickly adapt to the changing illumination in the background image sequence, and regional adaptation of moving object. Theoretical analysis and practice show that the algorithm has a good adaptability in a complex illumination environment, and real-time moving target detection accuracy has been improved significantly.
Keywords: background estimation Kalman filtering suppression of foreground adaptation
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