Investigating Spontaneous Facial Action Recognition through AAM Representations of the Face
Open accessAbstract
Face Recognition 276 actions.They typically occur in less controlled environments, with non-frontal pose, smaller face image size, small to moderate head movement, and less intense and often more complex facial actions.Spontaneous actions units are elicited indirectly from subjects through environmental variables (e.g., showing a subject something associated with happiness which then indirectly results in a smile).Although harder to collect and annotate, spontaneous facial actions are preferable to posed as they are representative of real world facial actions.Most automated facial action recognition systems have only been evaluated on posed facial action data [Donato et al., 1999, Tian et al., 2001] with only a small number of studies being conducted on spontaneous data [Braathen et al., 2001, Bartlett et al., 2005].This study extends much of the earlier work we conducted in [Lucey et al., 2006].We greatly expand upon our earlier work in a number of ways.First, we expand the number of AUs analyzed from 4, centered around the brow region, to 15, stemming from all regions of the face.Second, we investigate how representation affects both posed and spontaneous actions units by running our experiments across both kinds of datasets.Third, we report results in terms of verification performance (i.e., accept or reject that a claimed AU observation is that AU) rather than identification performance (i.e., determine out of a watchlist of AU combinations which class does this observation belong to?).The verification paradigm is preferable over identification as it provides a natural mechanism for dealing with simultaneously occurring AUs and is consistent with existing literature [Bartlett et al., 2005].
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Seel, N. M. (2012) · Springer eBooks · doi:10.1007/978-1-4419-1428-6_5195 · Cited by 19,525 · see citing works
Introduction to Statistical Pattern Recognition
(1990) · Elsevier eBooks · doi:10.1016/c2009-0-27872-x · Cited by 11,056 · 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
Zhao, W., Chellappa, R., Phillips, P. J., & Rosenfeld, A. (2003) · ACM Computing Surveys · doi:10.1145/954339.954342 · Cited by 6,174 · see citing works
Ekman, P., & Friesen, W. V. (2019) · PsycTESTS Dataset · doi:10.1037/t27734-000 · Cited by 6,019 · see citing works
Cootes, T. F., Edwards, G. J., & Taylor, C. J. (2001) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.927467 · Cited by 5,409 · see citing works
A Practical Guide to Support Vector Classication
Hsu, C., Chang, C.-C., & Lin, C. (2008) · Cited by 5,070 · see citing works
Comprehensive database for facial expression analysis
Takeo Kanade, A., Cohn, J. F., & Tian, Y. (2002) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/afgr.2000.840611 · Cited by 2,612 · see citing works
Duda, R. O., Hart, P. E. 1., & Stork, D. G. C. 2. /. J. (2001) · Cited by 2,469 · 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
Introduction to Statistical Pattern Recognition
Webb, A. R., & Copsey, K. D. (2011) · doi:10.1002/9781119952954.ch1 · Cited by 1,607 · see citing works
Active Appearance Models Revisited
Matthews, I., & Baker, S. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029666.37597.d3 · Cited by 1,538 · see citing works
Donato, G., Bartlett, M. S., Hager, J. C., Ekman, P., & B, T. J. S. A. (1999) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.799905 · Cited by 999 · see citing works
Face recognition: A literature survey
Arora, U. (2003) · ACM Computing Surveys · Cited by 794 · see citing works
Recognizing Facial Expression: Machine Learning and Application to Spontaneous Behavior
Bartlett, M. S., Littlewort, G. C., Frank, M. G., Lainscsek, C. S. M., Fasel, I., & Movellan, J. R. (2005) · 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.2005.297 · Cited by 632 · see citing works
(2017) · The SAGE Encyclopedia of Communication Research Methods · doi:10.4135/9781483381411.n178 · Cited by 559 · see citing works
Cohn, J. F., Zlochower, A. J., Lien, J. J.-J., & Takeo Kanade, A. (1999) · Psychophysiology · doi:10.1017/s0048577299971184 · Cited by 287 · see citing works
Takeo Kanade, A. (2005) · Lecture notes in computer science · doi:10.1007/11564386_1 · Cited by 226 · see citing works
Gibson, R. (2002) · Cited by 195 · see citing works
Machine learning methods for fully automatic recognition of facial expressions and facial actions
Bartlett, M. S., Littlewort, G. C., Lainscsek, C. S. M., Fasel, I., & Movellan, J. R. (2005) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/icsmc.2004.1398364 · Cited by 168 · see citing works
Recognizing Action Units for Facial Expression Analysis
Tian, Y., Kanade, T., & Colin, J. F. (2002) · Series in machine perception and artificial intelligence · doi:10.1142/9789812778543_0002 · Cited by 135 · see citing works
AAM Derived Face Representations for Robust Facial Action Recognition
Lucey, S., Matthews, I. A., Hu, C., Ambadar, Z., la Torre, F. D., & Cohn, J. F. (2006) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/fgr.2006.17 · Cited by 106 · see citing works
Self-citationCohn, J. F., Zlochower, A. J., Lien, J., et al. (2005) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195179644.003.0018 · Cited by 18 · see citing works
First steps towards automatic recognition of spontaneous facial action units
Braathen, B., Bartlett, M. S., Littlewort, G. C., et al. (2001) · doi:10.1145/971478.971515 · Cited by 12 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- S. Lucey, I.Matthews, C. Hu, Z. Ambadar, F. De la Torre, and J. Cohn. AAMderived face representations for robust facial action recognition. In IEEE International Conference on Automatic Face and Gesture Recognition (AFGR), pages 155-160, 2006.
Cited by
Sorted by citations
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
The painful face – Pain expression recognition using active appearance models
Ashraf, A. B., Lucey, S., Cohn, J. F., Chen, T., Ambadar, Z., Prkachin, K. M., & Solomon, P. E. (2009) · Image and Vision Computing · doi:10.1016/j.imavis.2009.05.007 · Cited by 355 · see citing works
Self-citationAutomatic detection of pain intensity
Hammal, Z., & Cohn, J. F. (2012) · Proceedings of the 14th ACM international conference on Multimodal interaction · doi:10.1145/2388676.2388688 · Cited by 185 · see citing works
A survey of affect recognition methods: audio, visual and spontaneous expressions
Zeng, Z., Pantic, M., Roisman, G. I., & Huang, T. S. (2007) · Proceedings of the 9th international conference on Multimodal interfaces · doi:10.1145/1322192.1322216 · Cited by 144 · see citing works
Error weighted semi-coupled hidden Markov model for audio-visual emotion recognition
Lin, J.-C., Wu, C.-H., & Wei, W.-L. (2012) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2011.2171334 · Cited by 121 · see citing works
- Authors
- Lucey, S., Bilal, A., & F., J.
- Affiliations
- Carnegie Mellon University (US)
- ORCID
- Lucey, Simon
- Venue
- Face Recognition
- Publisher
- I-Tech Education and Publishing
- Published
- 2007-07-01
- DOI
- 10.5772/4841
- OpenAlex
- W1596088243
- Cited by
- 161
- References
- 24
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 4 · 2022: 1 · 2021: 5 · 2020: 3 · 2019: 6 · 2018: 4 · 2017: 11 · 2016: 16 · 2015: 8 · 2014: 15 · 2013: 16 · 2012: 21
- FWCI
- 19.07
- Type
- book chapter
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by-nc-sa
- Locations
- BiblioBoard Library Catalog (Open Research Library) (submittedVersion, cc-by-sa)
- IntechOpen (submittedVersion, cc-by-nc-sa)
- 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 action unit recognition, active appearance models, face representation, non-frontal face images, head movement, facial expression recognition
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
