The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Action unit detection using sparse appearance descriptors in space-time video volumes
Abstract
Recently developed appearance descriptors offer the opportunity for efficient and robust facial expression recognition. In this paper we investigate the merits of the family of local binary pattern descriptors for FACS Action-Unit (AU) detection. We compare Local Binary Patterns (LBP) and Local Phase Quantisation (LPQ) for static AU analysis. To encode facial expression dynamics, we extend the purely spatial representation LPQ to a dynamic texture descriptor which we call Local Phase Quantisation from Three Orthogonal Planes (LPQ-TOP), and compare this with the Local Binary Patterns from Three Orthogonal Planes (LBP-TOP). The efficiency of these descriptors is evaluated by a fully automatic AU detection system and tested on posed and spontaneous expression data collected from the MMI and SEMAINE databases. Results show that the systems based on LPQ achieve higher accuracy rate than those using LBP, and that the systems that utilise dynamic appearance descriptors outperform those that use static appearance descriptors. Overall, our proposed LPQ-TOP method outperformed all other tested methods.
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Cites
Multiresolution gray-scale and rotation invariant texture classification with local binary patterns
Ojala, T., Pietikainen, M., & Maenpaa, T. (2002) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2002.1017623 · Cited by 15,398
A comparative study of texture measures with classification based on featured distributions
Ojala, T., Pietikäinen, M., & Harwood, D. (1996) · Pattern Recognition · doi:10.1016/0031-3203(95)00067-4 · Cited by 6,882
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
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
Cited by
Openface 2.0: facial behavior analysis toolkit
Baltrusaitis, T., Zadeh, A., Lim, Y. C., & Morency, L.-P. (2018) · 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018) · doi:10.1109/fg.2018.00019 · Cited by 1,861
McKeown, G., Valstar, M., Cowie, R., Pantic, M., & Schroder, M. (2012) · IEEE Transactions on Affective Computing · doi:10.1109/t-affc.2011.20 · Cited by 665
Self-citationThe first facial expression recognition and analysis challenge
Valstar, M. F., Jiang, B., Mehu, M., Pantic, M., & Scherer, K. (2011) · Face and Gesture 2011 · doi:10.1109/fg.2011.5771374 · Cited by 385
Self-citationIdentity-Aware Convolutional Neural Network for Facial Expression Recognition
Meng, Z., Liu, P., Cai, J., Han, S., & Tong, Y. (2017) · 2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017) · doi:10.1109/fg.2017.140 · Cited by 319
Meta-Analysis of the First Facial Expression Recognition Challenge
Valstar, M. F., Mehu, M., Jiang, B., Pantic, M., & Scherer, K. (2012) · IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) · doi:10.1109/tsmcb.2012.2200675 · Cited by 297
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Metadata
- Authors
- Jiang, B., Valstar, M. F., & Pantic, M.
- Venue
- Face and Gesture 2011
- Publisher
- IEEE
- Published
- 2011-03
- Pages
- 314-321
- OpenAlex
- W2143899944
- Cited by
- 233
- References
- 4
- FWCI
- 14.83
- Type
- conference paper
- Language
- en
- Open access
- closed
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