21 July 2017 Emotion recognition based on multiple order features using fractional Fourier transform
Author Affiliations +
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.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bo Ren, Deyin Liu, 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); doi: 10.1117/12.2281534; https://doi.org/10.1117/12.2281534
PROCEEDINGS
6 PAGES


SHARE
Back to Top