基于HOG和DMMA的单样本人脸识别

被引：9

作者：

杨秀坤

岳新启

汲清波

机构：

[1] 哈尔滨工程大学信息与通信工程学院

来源：

计算机应用研究 | 2015年 / 32卷 / 02期

基金：

黑龙江省自然科学基金;

关键词：

统计流形学习; 单样本; 方向梯度直方图; 多流形判别分析;

D O I：

暂无

中图分类号：

TP391.41 [];

学科分类号：

080203 ;

摘要：

为了提取复杂环境下人脸图像的有效特征,提出了一种结合DMMA(discriminative multi-manifold analysis)和方向梯度直方图(HOG)特征提取算法,利用了一种新的自适应方法计算子图像块的相似度。在DMMA算法中,将一幅样本图像分为不重叠的子图像块后,对每一个小块使用HOG算子进行处理,处理后形成一个统计流形,然后进行特征提取,利用基于重建的流形—流形间的距离最近邻方法进行分类识别。在AR人脸库和FERET人脸库上的实验结果表明,该算法对人脸图像的光照和几何变化比传统的DMMA算法识别性能更好。

引用

页码：627 / 629+634 +634

页数：4

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