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Emotion Recognition Method Using FLD and Staged Classification Based on Profile Data  

Kim, Jae-Hyup (Samsung Thales)
Oh, Na-Rae (Woori FIS)
Jun, Gab-Song (Samsung Thales)
Moon, Young-Shik (Dept. of Computer Science and Engineering, Hanyang University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.48, no.6, 2011 , pp. 35-46 More about this Journal
Abstract
In this paper, we proposed the method of emotion recognition using staged classification model and Fisher's linear discriminant. By organizing the staged classification model, the proposed method improves the classification rate on the Fisher's feature space with high complexity. The staged classification model is achieved by the successive combining of binary classification model which has simple structure and high performance. On each stage, it forms Fisher's linear discriminant according to the two groups which contain each emotion class, and generates the binary classification model by using Adaboost method on the Fisher's space. Whole learning process is repeatedly performed until all the separations of emotion classes are finished. In experimental results, the proposed method provides about 72% classification rate on 8 classes of emotion and about 93% classification rate on specific 3 classes of emotion.
Keywords
emotion recognition; FLD; Fisher's linear discriminant; Adaboost; staged classification;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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