结合HLBP模型与色彩位置信息的动目标检测方法

HLBP model method with color and location information about moving objects detection

为了克服抖动及目标阴影的影响,提高运动目标的检测精度,提出了一种简化的Haar-LBP(HLBP)模版,并以此为纹理模型,结合色彩和位置信息建立特征向量,在高斯混合模型下实现减背景的动目标检测算法.实验结果表明,该方法不仅能实时、准确地检测出运动目标,提高了阴影检出率,而且对相机引起的抖动具有较强的适应性.

This paper proposes a background subtraction algorithm using the Gaussian mixture model to combine multiple features which include the Haar‐LBP （ HLBP ） texture model , and color and location information . Experimental results validate the effectiveness of the proposed algorithm , which can not only detects an object timely and precisely , but also obtain a higher shadow detection rate and robustness to camera shake .