Two-dimensional neighborhood preserving embedding for face recognition

摘要：

Neighborhood Preserving Embedding (NPE) is a subspace learning algorithm, which has the ability of preserving local neighborhood structure on the data manifold. Though NPE has been applied in many domains of pattern recognition, it is a vectorbased method and will be encountered the small size sample (SSS) problem when it is directly applied to face recognition. To address this problem, the popular method is to use PCA prior to performing NPE, but the preprocessing procedure using PCA could result in the loss of some important discriminatory information. In this paper, a novel method called twodimensional neighborhood preserving embedding (2DNPE) is proposed to extract the features for face recognition. Extensive experiments are performed to test and evaluate the new method using ORL and Yale face database. The experimental results indicate that the 2DNPE method has better face recognition performance and more effective.

关键词： neighborhood preserving embedding(NPE) twodimensional neighborhood preserving embedding(2DNPE) subspace learning face recognition

作者: Haishun Du Sheng Wang Jianjun Zhao Na Xu

作者单位: Institute of Image Processing and Pattern RecognitionHenan UniversityKaifeng Henan, China Institute of Image Processing and Pattern Recognition Henan University Kaifeng Henan, China

会议类型: 国际会议

会议名称: 2010 2nd IEEE International Conference on Information Management and Engineering(2010年IEEE第二届信息管理与工程国际会议 IEEE ICIME 2010)

会议地点: 成都

会议语种:英文

页码: 1-5

在线出版日期: 2010-04-16（万方平台首次上网日期，不代表论文的发表时间）