A Novel Subspace Method for Face Recognition

摘要：

Feature extraction is the key problem for face recognition. Many methods have been proposed, and among these methods the subspace method has been given more and more attention owing to its good performance. In this paper, a novel subspace method called Inverse Fisher discriminant with Schur decomposition (IFDS) is proposed for face recognition. In comparison with Inverse Fisher discriminant analysis (IFDA), IFDS eliminates linear dependences among discriminant vectors. Experiments results on ORL and FERET face database demonstrate that IFDS outperforms Fisher discrimiant analysis (FDA) and IFDA algorithm.

关键词： Subspace method Fisher discriminant analysis face recognition feature extraction

作者: Yusheng Lin Guang Li

作者单位: The 54th Institute of the China Electronics Technology Group Corporation Beijing Institute of Techno The 54th Institute of the China Electronics Technology Group Corporation CETC54 Shijiazhuang, China

会议类型: 国际会议

会议名称: 2010 International Conference on Communications and Intelligence Information Security(2010年国际信息与智能安全学术会议 ICCIIS2010)

会议地点: 南宁

会议语种:英文

页码: 275-278

在线出版日期: 2010-10-13（万方平台首次上网日期，不代表论文的发表时间）