Combination of Local Multiple Patterns and Exponential Discriminant Analysis for Facial Recognition

• Main Authors: Lifang Zhou, Bin Fang, Weisheng Li, Lidou Wang
• Format: Article
• Language: English
• Published: IFSA Publishing, S.L. 2013-06-01
• Series: Sensors & Transducers
• Subjects: Face recognition; Local multiple pattern; Exponential discriminant analysis; Combination framework; Multiple classifier
• Online Access: http://www.sensorsportal.com/HTML/DIGEST/june_2013/P_1224.pdf

Global features-based methods and local features -based methods have been very successful in face recognition system, yet they can be combined together and jointly optimized so as to minimize the error of a nearest-neighbor classifier. We consider both descriptor for face images with Local Multiple Pattern, and discriminant learning techniques with Exponential Discriminant Analysis. A combination framework based on Local Multiple Pattern and Exponential Discriminant Analysis has been proposed in this paper. Firstly, our approach encodes the multi-scale face feature by Local Multiple Pattern, and then they have been extended to strengthen the discriminative ability by Exponential Discriminant Analysis; Secondly, we suggest to use the above feature on different layers independently so that a multiple classifier system can be attained. Using these techniques, we obtain the state-of-the-art performance on two public available databases.