Dynamic facial expression recognition by joint static and multi-time gap transition classification
Open accessAbstract
Automatic facial expression classification is a challenging problem for developing intelligent human-computer interaction systems. In order to take into account the expression dynamics, existing works usually make the assumption that a specific facial expression is displayed with a pre-segmented evolution, i.e. starting from neutral and finishing on an apex frame. In this paper, we propose a method to train a transition classifier from pairs of images. This transition classifier is applied at multiple time gaps and the output probabilities are fused along with a static estimation. We eventually show that our approach yields state-of-the-art accuracy on popular datasets without exploiting any such prior on the segmentation of the expression.
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- Authors
- Dapogny, A., Bailly, K., & Dubuisson, S.
- Affiliations
- Centre National de la Recherche Scientifique (FR)
- ORCID
- Dapogny, Arnaud
- Venue
- 2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)
- Publisher
- IEEE
- Published
- 2015-05
- Pages
- 1-6
- ISSN
- 1541-5058 (ISSN-L)
- OpenAlex
- W1486156117
- Cited by
- 24
- References
- 24
- Citations by year
- 2025: 1 · 2024: 1 · 2022: 2 · 2021: 2 · 2020: 5 · 2019: 1 · 2018: 3 · 2017: 4 · 2016: 4 · 2015: 1
- FWCI
- 5.34
- Type
- conference paper
- Language
- en
- Open access
- green
- hal.science
- Licence
- other-oa
- Locations
- International Conference on Automatic Face and Gesture Recognition (publishedVersion)
- HAL (submittedVersion, other-oa)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
- 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
- Keywords
- facial expression recognition, dynamic facial expressions, probability fusion, human-computer interaction
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