Automatic 3D Facial Expression Recognition Based on a Bayesian Belief Net and a Statistical Facial Feature Model
Abstract
Automatic facial expression recognition on 3D face data is still a challenging problem. In this paper we propose a novel approach to perform expression recognition automatically and flexibly by combining a Bayesian Belief Net (BBN) and Statistical facial feature models (SFAM). A novel BBN is designed for the specific problem with our proposed parameter computing method. By learning global variations in face landmark configuration (morphology) and local ones in terms of texture and shape around landmarks, morphable Statistic Facial feature Model (SFAM) allows not only to perform an automatic landmarking but also to compute the belief to feed the BBN. Tested on the public 3D face expression database BU-3DFE, our automatic approach allows to recognize expressions successfully, reaching an average recognition rate over 82%.
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- Authors
- Zhao, X., Huang, D., Dellandrea, E., & Chen, L.
- Affiliations
- École Centrale de Lyon (FR)
- Venue
- 2010 20th International Conference on Pattern Recognition
- Publisher
- IEEE
- Published
- 2010-08
- Pages
- 3724-3727
- ISSN
- 1041-3278 (ISSN-L)
- OpenAlex
- W2018776244
- Cited by
- 66
- References
- 17
- Citations by year
- 2026: 1 · 2025: 3 · 2023: 1 · 2022: 3 · 2021: 9 · 2020: 5 · 2019: 11 · 2018: 6 · 2017: 5 · 2016: 2 · 2015: 6 · 2014: 5 · 2013: 1 · 2012: 7
- FWCI
- 2.47
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition (publishedVersion)
- HAL (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face and Expression Recognition
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
- Keywords
- facial expression recognition, 3D face data, Bayesian networks, morphable face model, BU-3DFE, facial morphology
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