一种改进的混合高斯背景模型

An Improved Gaussian Mixture Model for Background Estimation

针对经典混合高斯模型无法识别静态目标的问题,提出一种改进算法。通过加入了参数还原算法,并引入一个反馈调节环节,可以避免静态前景被学习进入背景。当目标停留超过预定帧数时,目标所覆盖的每个像素点的K个高斯函数进行参数还原,避免了目标被更新为背景的一部分。实验结果表明,提出的改进模型,不仅能检测长时间静止目标,而且能识别多模态背景。

Traditional Adaptive Gaussian Mixture Model will lose target when deal with arbitrary-long stationary object. In this paper, a novel method for detecting this kind of object is proposed to improve the performance of Adaptive Gaussian Mixture Model. Para- meter restoration is designed to deal with arbitrary-long stationary target and solve the short-comings of the latest algorithm. Experi- mental results show that the proposed algorithm proves to be a more robust method by detecting the stationary target in an arbi- Wary-long time.