A new information fusion method for SVM-based robotic audio-visual emotion recognition

Meng Ju Han*, Jing Huai Hsu, Kai-Tai Song, Fuh Yu Chang

*Corresponding author for this work

研究成果: Conference contribution

11 引文 斯高帕斯(Scopus)

摘要

Emotion recognition has become an important research area for advanced human-robot interaction. Through recognizing facial expressions, a robot can interact with a person with a more friendly manner. In this paper, we proposed a bimodal emotion recognition system by combining image and speech information. A novel information fusion strategy is proposed to set proper weights to two feature modalities based on their recognition reliability. The fusion weights are determined by the distance between test data and the classification hyperplane and the standard deviation of training samples. After normalization using the mean distance between training samples and the hyperplane, the fusion weight is set to represent the classification reliability of individual modality. In the latter bimodal SVM classification, the recognition result with higher weight is selected. The complete procedure has been implemented in a DSP-based system to recognize five facial expressions on-line in real time. The experimental results show that a recognition rate of 86.9% is achieved, an improvement of 5% compared with using only image information.

原文English
主出版物標題2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007
頁面2656-2661
頁數6
DOIs
出版狀態Published - 1 十二月 2007
事件2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007 - Montreal, QC, Canada
持續時間: 7 十月 200710 十月 2007

出版系列

名字Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
ISSN(列印)1062-922X

Conference

Conference2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007
國家Canada
城市Montreal, QC
期間7/10/0710/10/07

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  • 引用此

    Han, M. J., Hsu, J. H., Song, K-T., & Chang, F. Y. (2007). A new information fusion method for SVM-based robotic audio-visual emotion recognition. 於 2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007 (頁 2656-2661). [4413990] (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics). https://doi.org/10.1109/ICSMC.2007.4413990