The DOI matches its Crossref record; 32 of the 34 references it cites were found in a registry or an index.
Automatic Facial Expression Recognition Using Facial Animation Parameters and Multistream HMMs
Abstract
The performance of an automatic facial expression recognition system can be significantly improved by modeling the reliability of different streams of facial expression information utilizing multistream hidden Markov models (HMMs). In this paper, we present an automatic multistream HMM facial expression recognition system and analyze its performance. The proposed system utilizes facial animation parameters (FAPs), supported by the MPEG-4 standard, as features for facial expression classification. Specifically, the FAPs describing the movement of the outer-lip contours and eyebrows are used as observations. Experiments are first performed employing single-stream HMMs under several different scenarios, utilizing outer-lip and eyebrow FAPs individually and jointly. A multistream HMM approach is proposed for introducing facial expression and FAP group dependent stream reliability weights. The stream weights are determined based on the facial expression recognition results obtained when FAP streams are utilized individually. The proposed multistream HMM facial expression system, which utilizes stream reliability weights, achieves relative reduction of the facial expression recognition error of 44% compared to the single-stream HMM system.
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In the citing paper
“Is is rarely used to parametrize FEs for recognition purposes [136], [137].”
From Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications (2016) · cites this paper as [137]
In the citing paper
“Most of these early works used geometric representations, like vectors for describing the motion of the face [134], active contours for describing the shape of the mouth and eyebrows [137], or deformable 2D mesh models [116].”
From Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications (2016) · cites this paper as [137]
Citations
Cites
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Rowley, H. A., Baluja, S., & Kanade, T. (1998) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.655647 · Cited by 3,554
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 2,644
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Example-based learning for view-based human face detection
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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 · cited 1×
“Several automatic facial expression and facial action recognition systems [29]–[ 33 ] utilize FACS as facial features.”
MethodFeature extraction from faces using deformable templates
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Research works printed but not linked: 6
- cohn, 1997, automated face coding: a computer-vision based method of facial expression analysis, 7th Eur Conf Facial Expression Measurement and Meaning, 329
- aleksic, 2005, automatic facial expression recognition using facial animation parameters and multi-stream hmms, 6th E Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS 05)
- suwa, 1978, a preliminary note on pattern recognition of human emotional expression, Proc 4th Int Joint Conf on Pattern Recognition, 408
- senior, 1999, face and feature finding for a face recognition system, Proc Int Conf Audio and Video Based Biometric Person Authentication, 154
- aleksic, 2003, an audio-visual person identification and verification system using faps as visual features, Proc Works Multimedia User Authentication, 80
- zhao, 1996, classifying facial emotions by back propagation neural networks with fuzzy inputs, Proc Int Conf Neural Inform Process, 1, 454
Cited by
Sorted by citations
Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions
Zhao, G., & Pietikainen, M. (2007) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2007.1110 · Cited by 2,846
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
Facial expression recognition using radial encoding of local Gabor features and classifier synthesis
Gu, W., Xiang, C., Venkatesh, Y. V., Huang, D., & Lin, H. T. (2011) · Pattern Recognition · doi:10.1016/j.patcog.2011.05.006 · Cited by 312
Face Expression Recognition and Analysis: The State of the Art
Bettadapura, V. (2012) · arXiv · doi:10.48550/arxiv.1203.6722 · Cited by 336
Facial Expression Recognition Using Facial Movement Features
Zhang, L., & Tjondronegoro, D. (2011) · IEEE Transactions on Affective Computing · doi:10.1109/t-affc.2011.13 · Cited by 253
Metadata
- Authors
- Aleksic, P. S., & Katsaggelos, A. K.
- Affiliations
- Northwestern University (US)
- ORCID
- Katsaggelos, A.K.
- Venue
- IEEE Transactions on Information Forensics and Security
- Published
- 2006-03
- Volume
- 1
- Issue
- 1
- Pages
- 3-11
- ISSN
- 1556-6013 (ISSN-L)
- OpenAlex
- W2098044144
- Cited by
- 235
- References
- 34
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 4 · 2023: 3 · 2022: 11 · 2021: 1 · 2020: 14 · 2019: 8 · 2018: 7 · 2017: 15 · 2016: 11 · 2015: 20 · 2014: 19 · 2013: 19 · 2012: 12
- FWCI
- 24.02
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Information Forensics and Security (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › 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, facial animation parameters, eyebrow movements, MPEG-4, error reduction
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