Directional two-dimensional neighborhood preserving projection for face recognition

摘要：

This paper presents a novel manifold learning method, namely Directional two-dimensional neighborhood preserving embedding (Dir-2DNPE), for feature extraction. In contrast to standard NPE, Dir-2DNPE directly seeks the optimal projective vectors from the directional images without image-to-vector transformation. Moreover, Dir-2DNPE can well reserve the spatial correlations between variations of rows and those of columns of images. Experiments on the ORL and Yale databases show the effectiveness of the proposed method.

关键词： Neighborhood preserving embedding (NPE) Directional-image 2-Dimensional NPE Dir-2DNPE face recognition

作者: Li Yiying Tian Qichuan Gao Quanxue Xu jing

作者单位: Key Laboratory on Integrated Services Networks, XIDIAN University Xian,China School of Electronic Information Engineering, Taiyuan University of Science and technology, Taiyuan,

会议类型: 国际会议

会议名称: International Conference on Computational Aspects of Social Networks(国际社会网络计算会议 CASoN 2010)

会议地点: 太原

会议语种:英文

页码: 357-360

在线出版日期: 2010-09-26（万方平台首次上网日期，不代表论文的发表时间）