Face Recognition Based on the Statistics Methods

摘要：

In many face recognition methods, the ones based on the statistics theory are more commonly used and proved to be effective. This paper introduces two of these methods: an improved method named weighted modular Two-dimensional Principal Component Analysis (WM-2DPCA) and Bayesian classifier. And then combine the advantages of these two methods and apply them to face recognition. Experimental results show that the combined method can be used successfully in face recognition, and also illustrate the effectiveness of the combination.

关键词： face recognition statistics WM-2DPCA Bayesian combination

作者: Lijing Zhang Ying Zhang

作者单位: Network Administration Center North China Electric Power University Baoding,071003,Hebei Province,Ch Department of Computer Science North China Electric Power University Baoding,071003,Hebei Province,C

会议类型: 国际会议

会议名称: The 3rd International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2009)(第三届生物信息与生物医学工程国际会议)

会议地点: 北京

会议语种:英文

页码: 1-4

在线出版日期: 2009-06-11（万方平台首次上网日期，不代表论文的发表时间）