Comparative evaluation of 3D vs. 2D modality for automatic detection of facial action units
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Most 3D methods target primary expressions but studies about AUs were published as well.
“Most of them target primary expressions [131] but studies about AUs were published as well [122], [218].”
From Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications (2016) · cites this paper as [218]
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Cites
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
Recognizing action units for facial expression analysis
Tian, Y.-I., Kanade, T., & Cohn, J. F. (2001) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.908962 · Cited by 1,745 · see citing works
Is the startle reaction an emotion
Ekman, P., Friesen, W. V., & Simons, R. C. (1985) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.49.5.1416 · Cited by 202 · see citing works
3D facial expression recognition based on automatically selected features
Tang, H., & Huang, T. S. (2008) · 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops · doi:10.1109/cvprw.2008.4563052 · Cited by 140 · see citing works
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Corneanu, C. A., Simon, M. O., Cohn, J. F., & Guerrero, S. E. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2515606 · Cited by 527 · see citing works
Static and dynamic 3D facial expression recognition: A comprehensive survey
Sandbach, G., Zafeiriou, S., Pantic, M., & Yin, L. (2012) · Image and Vision Computing · doi:10.1016/j.imavis.2012.06.005 · Cited by 357 · see citing works
Local normal binary patterns for 3D facial action unit detection
Sandbach, G., Zafeiriou, S., & Pantic, M. (2012) · 2012 19th IEEE International Conference on Image Processing · doi:10.1109/icip.2012.6467234 · Cited by 56 · see citing works
Temporal Bayesian Fusion for Affect Sensing: Combining Video, Audio, and Lexical Modalities
Savran, A., Cao, H., Nenkova, A., & Verma, R. (2015) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2014.2362101 · Cited by 53 · see citing works
Self-citationZhao, X., Dellandréa, E., Zou, J., & Chen, L. (2013) · Image and Vision Computing · doi:10.1016/j.imavis.2012.10.001 · Cited by 27 · see citing works
- Authors
- Savran, A., Sankur, B., & Taha Bilge, M.
- Affiliations
- Boğaziçi University (TR)
- Corresponding author
- Savran, Arman
- Venue
- Pattern Recognition
- Publisher
- Elsevier BV
- Published
- 2012-02
- Volume
- 45
- Issue
- 2
- Pages
- 767-782
- ISSN
- 0031-3203 (ISSN-L)
- OpenAlex
- W2130571344
- Cited by
- 111
- References
- 4
- Citations by year
- 2025: 6 · 2024: 3 · 2023: 5 · 2022: 4 · 2021: 7 · 2020: 11 · 2019: 10 · 2018: 6 · 2017: 6 · 2016: 7 · 2015: 14 · 2014: 14 · 2013: 9 · 2012: 7
- FWCI
- 11.01
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Pattern Recognition (publishedVersion)
- Funders
- Türkiye Bilimsel ve Teknolojik Araştırma Kurumu
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face and Expression Recognition
- Keywords
- facial action units, facial expression recognition, 3D face data, facial action coding system, multimodal fusion, feature selection, classifier comparison
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