Semi-supervised Two-dimensional Manifold Learning Based on Pair-wise Constraints

摘要：

　　LLTSA),this paper proposed a Semi-supervised two-dimensional manifold learning based on pair-wise constraints(2D-PCLTSA).2D-PCLTSA adopts two-dimensional image matrices as the samples to extract image feature information,and uses pair-wise constraints as supervised information.2D-PCLTSA preserves the feature information in the sample set while taking advantage of the supervised information effectively.Through the experiments on YALE and ORL,2D-PCLTSA outperforms based on traditional dimensionality reduction algorithms with maximum average recognition rate by 2.85%and 6.25%respectively.Especially,our algorithm could keep well classification performance with a few constraints.

关键词： semi-supervised learning pair-wise constraints tangent space eigen-decomposition face recognition

作者: XUE Wei WANG Zheng-qun LI Feng ZHOU Zhong-xia

作者单位: Department of Information and Engineering,Yang zhou university,Yangzhou 225127,China

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 4807-4811

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）