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http://dx.doi.org/10.5391/JKIIS.2010.20.6.7.806

Facial Expression Recognition by Combining Adaboost and Neural Network Algorithms  

Hong, Yong-Hee (숭실대학교 전자공학과)
Han, Young-Joon (숭실대학교 전자공학과)
Hahn, Hern-Soo (숭실대학교 전자공학과)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.20, no.6, 2010 , pp. 806-813 More about this Journal
Abstract
Human facial expression shows human's emotion most exactly, so it can be used as the most efficient tool for delivering human's intention to computer. For fast and exact recognition of human's facial expression on a 2D image, this paper proposes a new method which integrates an Discrete Adaboost classification algorithm and a neural network based recognition algorithm. In the first step, Adaboost algorithm finds the position and size of a face in the input image. Second, input detected face image into 5 Adaboost strong classifiers which have been trained for each facial expressions. Finally, neural network based recognition algorithm which has been trained with the outputs of Adaboost strong classifiers determines final facial expression result. The proposed algorithm guarantees the realtime and enhanced accuracy by utilizing fastness and accuracy of Adaboost classification algorithm and reliability of neural network based recognition algorithm. In this paper, the proposed algorithm recognizes five facial expressions such as neutral, happiness, sadness, anger and surprise and achieves 86~95% of accuracy depending on the expression types in real time.
Keywords
Adaboost; Neural Network; Facial Expression Recognition; Haar-like Feature; Pattern Classification;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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