Expression recognition from 3D dynamic faces using robust spatio-temporal shape features
Open accessAbstract
This paper proposes a new method for comparing 3D facial shapes using facial level curves. The pair- and segment-wise distances between the level curves comprise the spatio-temporal features for expression recognition from 3D dynamic faces. The paper further introduces universal background modeling and maximum a posteriori adaptation for hidden Markov models, leading to a decision boundary focus classification algorithm. Both techniques, when combined, yield a high overall recognition accuracy of 92.22% on the BU-4DFE database in our preliminary experiments. Noticeably, our feature extraction method is very efficient, requiring simple preprocessing, and robust to variations of the input data quality.
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A tutorial on hidden Markov models and selected applications in speech recognition
Rabiner, L. R. (1989) · Proceedings of the IEEE · doi:10.1109/5.18626 · Cited by 22,743 · see citing works
Seel, N. M. (2012) · Springer eBooks · doi:10.1007/978-1-4419-1428-6_5195 · Cited by 19,525 · see citing works
Pattern Recognition and Machine Learning
(2007) · Kybernetes · doi:10.1108/03684920710743466 · Cited by 8,540 · see citing works
Russell, E. L., Chiang, L. H., & Braatz, R. D. (2000) · Advances in industrial control · doi:10.1007/978-1-4471-0409-4_3 · Cited by 7,938 · see citing works
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
Zeng, Z., Pantic, M., Roisman, G. I., & Huang, T. S. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2008.52 · Cited by 2,797 · see citing works
Self-citationDuda, R. O., Hart, P. E. 1., & Stork, D. G. C. 2. /. J. (2001) · Cited by 2,469 · see citing works
Book Review: Pattern Recognition and Machine Learning
Nasrabadi, N. M. (2007) · Journal of Electronic Imaging · doi:10.1117/1.2819119 · Cited by 636 · see citing works
A high-resolution 3D dynamic facial expression database
Yin, L., Chen, X., Sun, Y., Worm, T., & Reale, M. (2008) · 2008 8th IEEE International Conference on Automatic Face & Gesture Recognition · doi:10.1109/afgr.2008.4813324 · Cited by 488 · see citing works
Analysis of planar shapes using geodesic paths on shape spaces
Klassen, E. P., Srivastava, A., Mio, W., & Joshi, S. K. (2004) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2004.1262333 · Cited by 479 · see citing works
Three-Dimensional Face Recognition
Bronstein, A. M., Bronstein, M. M., & Kimmel, R. (2005) · International Journal of Computer Vision · doi:10.1007/s11263-005-1085-y · Cited by 425 · see citing works
3D Facial Expression Recognition Based on Primitive Surface Feature Distribution
Wang, J., Yin, L., Wei, X., & Sun, Y. (2006) · 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (CVPR'06) · doi:10.1109/cvpr.2006.14 · Cited by 307 · see citing works
Three-Dimensional Face Recognition Using Shapes of Facial Curves
Samir, C., Srivastava, A., & Daoudi, M. (2006) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2006.235 · Cited by 219 · 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
Self-citationFeature-centric evaluation for efficient cascaded object detection
Schneiderman, H. (2004) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2004.1315141 · Cited by 137 · see citing works
Facial Expression Recognition Based on 3D Dynamic Range Model Sequences
Sun, Y., & Yin, L. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-88688-4_5 · Cited by 120 · see citing works
Tang, H., & Huang, T. S. (2008) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/afgr.2008.4813304 · Cited by 107 · see citing works
Self-citationAn Intrinsic Framework for Analysis of Facial Surfaces
Samir, C., Srivastava, A., Daoudi, M., et al. (2008) · International Journal of Computer Vision · doi:10.1007/s11263-008-0187-8 · Cited by 101 · see citing works
Learning a restricted bayesian network for object detection
Schneiderman, H. (2004) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2004.1315224 · Cited by 90 · see citing works
Reynolds, D. A. (2009) · Springer eBooks · doi:10.1007/978-0-387-73003-5_197 · Cited by 33 · see citing works
Bilinear elastically deformable models with application to 3D face and facial expression recognition
Mpiperis, I., Malassiotis, S., & Strintzis, M. G. (2008) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/afgr.2008.4813333 · Cited by 21 · 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
Hayat, M., Bennamoun, M., & El-Sallam, A. A. (2013) · 2013 IEEE Workshop on Applications of Computer Vision (WACV) · doi:10.1109/wacv.2013.6475003 · Cited by 14 · see citing works
- Authors
- Le, V., Tang, H., & Huang, T. S.
- Affiliations
- University of Illinois Urbana-Champaign (US)
- Venue
- Face and Gesture 2011
- Publisher
- IEEE
- Published
- 2011-03
- Pages
- 414-421
- ISSN
- 1541-5058 (ISSN-L)
- OpenAlex
- W2060515346
- Cited by
- 67
- References
- 20
- Citations by year
- 2024: 1 · 2023: 2 · 2022: 1 · 2021: 2 · 2020: 3 · 2019: 3 · 2018: 5 · 2017: 6 · 2016: 9 · 2015: 7 · 2014: 7 · 2013: 9 · 2012: 9
- FWCI
- 6.69
- Type
- conference paper
- Language
- en
- Open access
- green
- figshare.com
- Licence
- cc-by
- Locations
- International Conference on Automatic Face and Gesture Recognition (publishedVersion)
- Figshare (submittedVersion, cc-by)
- 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, maximum a posteriori adaptation, hidden Markov models
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