Recognition of facial expressions using HMM with continuous output probabilities
Abstract
Facial expression recognition is an important technology fundamental to realize intelligent image coding systems and advanced man-machine interfaces in visual communication systems. In the computer vision field, many techniques have been developed to recognize facial expressions. However, most of these techniques are based on static features extracted from one or two still images. Those techniques are not robust against noise and cannot recognize subtle changes in facial expressions. In this paper we use hidden Markov models (HMM) with continuous output probabilities to extract a temporal pattern of facial motion. In order to improve the recognition performance, we propose a new feature obtained from wavelet transform coefficients. For the evaluation, we use 180 image sequences taken from three male subjects. Using these image sequences, the recognition rate for user trained mode achieved 98% compared with 84% using our previous method. The recognition rate for user independent mode achieved 84% when the expressions were restricted to four expressions.
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The Otsuka and Ohya HMM was trained on 120 image sequences shown by two male subjects and tested on image sequences shown by the same subjects.
“The HMM was trained on 120 image sequences, shown by two male subjects.The method was tested on image sequences shown by the same subjects.”
From Automatic analysis of facial expressions: the state of the art (2000) · cites this paper as [60]
Cites
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Automatic analysis of facial expressions: the state of the art
Pantie, M., & Rothkrantz, L. J. M. (2000) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.895976 · Cited by 1,778 · see citing works
Spotting segments displaying facial expression from image sequences using HMM
Otsuka, T., & Ohya, J. (2002) · Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition · doi:10.1109/afgr.1998.670988 · Cited by 69 · see citing works
Self-citation
- Authors
- Otsuka, T., & Ohya, J.
- Affiliations
- Advanced Telecommunications Research Institute International (JP)
- ORCID
- Otsuka, T.
- Venue
- Proceedings 5th IEEE International Workshop on Robot and Human Communication. RO-MAN'96 TSUKUBA
- Publisher
- IEEE
- Published
- 2002-12-24
- Pages
- 323-328
- ISSN
- 1944-9437 (ISSN-L)
- OpenAlex
- W2165750466
- Cited by
- 35
- References
- 13
- Citations by year
- 2026: 1 · 2019: 1 · 2016: 2 · 2014: 3 · 2013: 4 · 2012: 1
- FWCI
- 2.01
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE RO-MAN (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face and Expression Recognition
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
- Keywords
- facial expression recognition, hidden Markov models, facial motion, wavelet coefficients, temporal feature extraction, user-independent recognition, image sequences
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