Research of Face Recognition Method Based on Multiple Classifier Fusion

摘要：

　　In this paper,a recognition method for multiple classifiers is proposed,which combines an improved eigenface method with Support Vector Machine(SVM).The combining classifiers can make use of high recognition rate for SVM and high speed for distance classification.The distance classifier may classify the input images and give the final results when the rejecting rule is satisfied.Otherwise,these images are delivered to SVM for further classification.Experiment data show that the fusion of multiple classifiers for face recognition has higher efficiency,accuracy of recognition and lower rate of error recognition.

关键词： Face recognition Multiple classifier combination An improved eigenface method Principal Component Analysis(PCA) Support Vector Machine

作者: Yu-Long Xu Yong-mei Zhang

作者单位: School of Computer Science and Technology, Civil Aviation University of China Tianjin,China School of Information Engineering, North China University of Technology Beijing, China

会议类型: 国际会议

会议名称: 2012 2nd international Conference on Materials Science and Information Technology(2012第二届材料科学与信息技术国际会议)(MSIT2012)

会议地点: 西安

会议语种:英文

页码: 1075-1079

在线出版日期: 2012-08-24（万方平台首次上网日期，不代表论文的发表时间）