摘要
等度规映射算法旨在最大限度地保持样本间距离,没有考虑样本的类判别信息。针对该问题,提出一种基于判别等度规映射的人脸识别算法。在等度规映射算法的基础上,引入最大散度差准则,得到优化的目标函数。在嵌入低维子空间后,同类样本保持其固有的近邻几何结构关系,不同类近邻样本则彼此远离。在ORL数据库上的实验结果验证了该算法的有效性。
Isometric Projection（IsoP） algorithm aims at preserving the distance among samples at the most, without taking into account the sample class discriminant information. Aiming at this problem, a face recognition algorithm based on Discriminant Isometric Projection（DlsoP） is proposed. The algorithm is based on IsoP and the Maximum Scatter Difference Criterion（MSDC） is introduced to its objective function. Therefore, an optimal objective function is obtained. After being embedded into a low-dimensional subspace, the samples of same class maintain their intrinsic neighbor relations, whereas the neighboring samples of the different class are far form each other. Experimental results on ORL face database demonstrate the effectiveness of the proposed algorithm.
出处
《计算机工程》
CAS
CSCD
2012年第16期14-17,共4页
Computer Engineering
基金
河南省高等学校青年骨干教师资助计划基金资助项目(2011GGJS-173)
关键词
等度规映射
人脸识别
特征提取
最大散度差准则
Isometric Projection（IsoP）
face recognition
feature extraction
Maximum Scatter Difference Criterion（MSDC）
