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Facial emotion recognition using multi-modal information
Abstract
Facial emotion recognition will become vitally important in future multi-cultural visual communication systems, for emotion translation between cultures, which may be considered analogous to speech translation. However so far the recognition of facial emotions is mainly addressed by computer vision researchers, based on facial display. Also detection of vocal expressions of emotions can be found in research work done by acoustic researchers. Most of these research paradigms are devoted purely to visual or purely to auditory human emotion detection. However we found that it is very interesting to consider both these auditory and visual information together, for processing, since we hope this kind of multi-modal information processing will become a datum of information processing in future multimedia era. By several intensive subjective evaluation studies we found that human beings recognise anger, happiness, surprise and dislike by their visual appearance, compared to voice only detection. When the audio track of each emotion clip is dubbed with a different type of auditory emotional expression, still anger, happiness and surprise were video dominant. However the dislike emotion gave mixed responses to different speakers. In both studies we found that sadness and fear emotions were audio dominant. As a conclusion, we propose a method of facial emotion detection by using a hybrid approach, which uses multi-modal information for facial emotion recognition.
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“The method proposed by Cohn et al. deals neither with image sequences containing several facial actions in a row, nor with inaccurate facial data, nor with facial action intensity (yet the concept of the method makes it possible).”
From Automatic analysis of facial expressions: the state of the art (2000) · cites this paper as [10]
In the citing paper
“The accuracy of the classification was 92 percent for the eyebrow region, 88 percent for the eye region and 83 percent for the nose/ mouth region.”
From Automatic analysis of facial expressions: the state of the art (2000) · cites this paper as [10]
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Metadata
- Authors
- De Silva, L. C., Miyasato, T., & Nakatsu, R.
- Affiliations
- Advanced Telecommunications Research Institute International (JP)
- ORCID
- Nakatsu, R.
- Venue
- Proceedings of ICICS, 1997 International Conference on Information, Communications and Signal Processing. Theme: Trends in Information Systems Engineering and Wireless Multimedia Communications (Cat. No.97TH8237)
- Publisher
- IEEE
- Published
- 2002-11-22
- Volume
- 1
- Pages
- 397-401
- OpenAlex
- W2154739180
- Cited by
- 319
- References
- 9
- Citations by year
- 2026: 2 · 2025: 10 · 2024: 16 · 2023: 16 · 2022: 39 · 2021: 16 · 2020: 18 · 2019: 11 · 2018: 25 · 2017: 11 · 2016: 18 · 2015: 15 · 2014: 8 · 2013: 8 · 2012: 12
- FWCI
- 13.69
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Information, Communications & Signal Processing (ICICS) (publishedVersion)
- National University of Singapore (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
- Physical Sciences › Computer Science › Signal Processing › Speech and Audio Processing
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
- Keywords
- facial emotion recognition, multimodal emotion recognition, vocal emotion expression
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