Emotion Recognition Method Based on Multimodal Sensor Fusion Algorithm
- Authors
- 문병현; 심귀보
- Issue Date
- 2008
- Publisher
- 한국지능시스템학회
- Keywords
- Recognition; Principal Component Analysis (PCA); Multimodal; Decision Fusion Method
- Citation
- International Journal of Fuzzy Logic and Intelligent systems, v.8, no.2, pp 105 - 110
- Pages
- 6
- Journal Title
- International Journal of Fuzzy Logic and Intelligent systems
- Volume
- 8
- Number
- 2
- Start Page
- 105
- End Page
- 110
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/31462
- ISSN
- 1598-2645
- Abstract
- Human being recognizes emotion fusing information of the other speech signal, expression, gesture and bio-signal. Computer needs technologies that being recognized as human do using combined information. In this paper, we recognized five emotions (normal, happiness, anger, surprise, sadness) through speech signal and facial image, and we propose to method that fusing into emotion for emotion recognition result is applying to multimodal method. Speech signal and facial image does emotion recognition using Principal Component Analysis (PCA) method. And multimodal is fusing into emotion result applying fuzzy membership function. With our experiments, our average emotion recognition rate was 63% by using speech signals, and was 53.4% by using facial images. That is, we know that speech signal offers a better emotion recognition rate than the facial image. We proposed decision fusion method using S-type membership function to heighten the emotion recognition rate. Result of emotion recognition through proposed method, average recognized rate is 70.4%. We could know that decision fusion method offers a better emotion recognition rate than the facial image or speech signal.
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Collections - College of ICT Engineering > School of Electrical and Electronics Engineering > 1. Journal Articles
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