Emotion recognition based on multiple order features using fractional Fourier transform

Bo Ren; Deyin Liu; Lin Qi

doi:10.1117/12.2281534

21 July 2017 Emotion recognition based on multiple order features using fractional Fourier transform

Bo Ren, Deyin Liu, Lin Qi

Proceedings Volume 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017); 1042008 (2017) https://doi.org/10.1117/12.2281534
Event: Ninth International Conference on Digital Image Processing (ICDIP 2017), 2017, Hong Kong, China

Abstract

In order to deal with the insufficiency of recently algorithms based on Two Dimensions Fractional Fourier Transform (2D-FrFT), this paper proposes a multiple order features based method for emotion recognition. Most existing methods utilize the feature of single order or a couple of orders of 2D-FrFT. However, different orders of 2D-FrFT have different contributions on the feature extraction of emotion recognition. Combination of these features can enhance the performance of an emotion recognition system. The proposed approach obtains numerous features that extracted in different orders of 2D-FrFT in the directions of x-axis and y-axis, and uses the statistical magnitudes as the final feature vectors for recognition. The Support Vector Machine (SVM) is utilized for the classification and RML Emotion database and Cohn-Kanade (CK) database are used for the experiment. The experimental results demonstrate the effectiveness of the proposed method.

Citation Download Citation

Bo Ren, Deyin Liu, and Lin Qi "Emotion recognition based on multiple order features using fractional Fourier transform", Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 1042008 (21 July 2017); https://doi.org/10.1117/12.2281534

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