基于纹理特征改进的GFL运动目标提取方法

Improved GFL Moving Target Extraction Method Based on Texture Features

基于广义融合套索(GFL)前景模型,融合视频的纹理特征,提出一种基于纹理特征的运动目标提取方法。方法通过GFL前景模型提取前景运动目标和背景,再利用LBP算法提取前景与背景在多个方向上的纹理特征,比较两者纹理特征的相似度,去除前景中的投射阴影,解决由于运动目标遮挡产生的阴影问题,同时还引入误判率去描述模型的准确度。通过对广场、办公室以及体育馆等实际场景进行测试,实验表明提出的算法能够有效去除运动目标产生的阴影。

Based on Generalized Fused Lasso(GFL)foreground model and the texture information of video,this paper proposes a moving target extraction method based on texture features.This method uses GFL foreground model to extract foreground moving object and background.Then it extracts the texture features of foreground and background in many directions by LBP algorithm,compares the similarity of two texture features,and removes the misjudged shadow regions in the foreground,which can reduce the cast shadows due to occlusion of moving targets.The paper also introduces the misjudgment rate to describe the accuracy of model.By testing real scenes that contain cast shadows,such as squares,offices,and gymnasiums,the proposed algorithm can effectively monitor the areas where shadows are cast.