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中国图象图形学报 2015

复杂场景下自适应背景减除算法

DOI: 10.11834/jig.20150604

邵奇可,周宇,李路,陈庆章

Keywords: 背景减除,混合高斯模型,onlineK-means,onlineEM,灰度值

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Abstract:

目的复杂场景下的背景减除是智能视频监控研究领域的研究重点和热点之一.针对混合高斯模型中高斯分布个数固定和参数初始化粗糙问题,提出一种应用于复杂场景中的基于混合高斯模型的自适应背景减除算法(AMGBS).方法通过灰度值归类算法自适应调整模型的高斯分布个数,使得背景模型能够适应场景的变化,并且结合在线K均值(onlineK-means)算法和在线期望最大化(onlineEM)算法初始化混合高斯模型参数.结果针对灰度值统计结果调整高斯分布数,以及采用优化参数初始化过程,实验表明,本文方法的平均查准率和平均查全率比传统的混合高斯算法高出10%左右,比其他改进的混合高斯算法高出2%左右.结论提出一种新的自适应背景减除算法,针对灰度值统计结果调整高斯分布数,以及采用优化参数初始化过程.实验结果表明,该方法对复杂场景有较强的适应能力,能够有效快速地完成背景减除,进而实现运动目标的提取.

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