Face Recognition based on LFA features and DLPP Algorithm

摘要：

Some research efforts have shown that face images possibly reside on a nonlinear sub-manifold. Laplacianfaces explicitly considers the manifold structure of the face image. To avoid the singular problem, Laplacianfaces method first project the image vectors to PCA subspaces. However, PCA produces global non-topographic linear filters. In this paper, we propose a novel approach by combining LFA features and DLPP algorithm. LFA can capture local characteristics with little lose of global information and present an effective and robust representation of face images. DLPP avoids the singular problem in LPP, and doesn’t need a PCA transform in advance. Moreover, the new algorithm avoids selecting the subset of LFA features which is difficult and time consuming. A series of experiments show that our algorithm outperforms than Laplacianfaces and has explicit significance.

关键词： LFA LPP DLPP Face Recognition

作者: Jiangfeng Chen Baozong Yuan Bo Li

作者单位: Institute of Information Science,Beijing Jiaotong University,Beijing,China 100044

会议类型: 国际会议

会议名称: The IET 2nd International Conference on Wireless,Mobile & Multimedia Networks(第二届IET国际无线移动多媒体网络会议)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-12（万方平台首次上网日期，不代表论文的发表时间）