Title :
Face Recognition Based on the Statistics Methods
Author :
Zhang, Lijing ; Zhang, Ying
Author_Institution :
Network Adm. Center, North China Electr. Power Univ., Baoding, China
Abstract :
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.
Keywords :
Bayes methods; face recognition; image classification; principal component analysis; Bayesian classifier; WM-2DPCA; face recognition; statistics method; weighted modular two-dimensional principal component analysis; Bayesian methods; Computer science; Covariance matrix; Face recognition; Feature extraction; Gaussian distribution; Principal component analysis; Probability; Statistical distributions; Statistics;
Conference_Titel :
Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009. 3rd International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2901-1
Electronic_ISBN :
978-1-4244-2902-8
DOI :
10.1109/ICBBE.2009.5162845
