一种改进的基于纹理的局部二值模式背景减法

Guodong Tian, Aidong Men
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引用次数: 5

摘要

(1)中提出的基于纹理的局部二值模式(LBP)方法是一种成功的背景减除方法,尤其适用于动态背景场景。然而,它通常存在分割结果形状不准确和对当前情况适应缓慢的问题。在本文中,我们提出了一种改进的TBM,解决了这两个问题。为了解决第一个问题,提出了一个空间加权LBP直方图(SWLH)作为特征向量,并引入了一种简单的阴影去除方法。在处理第二种情况时,我们对每个模型的LBP直方图使用自适应学习率,并保持多个帧级模型来处理突然的光照变化。实验结果表明,该方法优于原TBM。
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An Improved Texture-Based Method for Background Subtraction Using Local Binary Patterns
Texture-based method (TBM) using local binary patterns (LBP) proposed in (1) is a successful solution to background subtraction especially for dynamic background scenes. However, it usually suffers from inaccuracy of the shapes of segmentation results and slow adaptation to the current situation. In this paper, we present an improved TBM that solves the two problems. To solve the first problem, a spatially weighted LBP histogram (SWLH) is proposed to be the feature vector and a simple shadow removing method is introduced. When dealing with the second one, we use an adaptive learning rate for each model LBP histogram and maintain multiple frame level models to process sudden illumination changes. Experimental results show that the proposed method outperforms the original TBM.
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