Face Recognition Using Eigenfaces

摘要：

Face is a complex multidimensional visual model and developing a computational model for face recognition is difficult. The paper presents a methodology for face recognition based on information theory approach of coding and decoding the face image. Proposed methodology is connection of two stages — Feature extraction using Principle Component Analysis and recognition using the feed forward back propagation Neural Network. The goal is to implement the system (model) for a particular face and distinguish it from a large number of stored faces with some real-time variations as well. The Eigenface approach uses Principal Component Analysis (PCA) algorithm for the recognition of the images. It gives us efficient way to find the lower dimensional space.

关键词： Face Recognition Principal Component Analysis Eigenfaces Eigen values Eigenvector

作者: V.P. Kshirsagar M.R.Baviskar M.E.Gaikwad

作者单位: Dept. of CSE,Govt. Engineering College, Aurangabad (MS), India

会议类型: 国际会议

会议名称: 2011 3rd IEEE International Conference on Computer Research and Development(ICCRD 2011)(2011第三届计算机研究与发展国际会议)

会议地点: 上海

会议语种:英文

页码: 302-306

在线出版日期: 2011-03-11（万方平台首次上网日期，不代表论文的发表时间）