The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
Recognizing Facial Expressions in Image Sequences Using Local Parameterized Models of Image Motion
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The importance of facial dynamics in FER has been established in many vision experiments.
“The importance of facial dynamics in FER has been established in many vision experiments [16,19].”
From Multimodal learning for facial expression recognition (2015) · cites this paper as [19]
In Black and Yacoob's approach, the initial regions for the head and the facial features were selected by hand and thereafter automatically tracked.
“In the approach proposed by Black and Yacoob, the initial regions for the head and the facial features were selected by hand and thereafter automatically tracked.”
From Automatic analysis of facial expressions: the state of the art (2000) · cites this paper as [2]
Lip biting is sometimes mistakenly identified as a smile by the Black and Yacoob method.
“ªLip bitingº is sometimes mistakenly identified as a smile [2].”
From Automatic analysis of facial expressions: the state of the art (2000) · cites this paper as [2]
The Black and Yacoob method does not deal with blends of emotional expressions; for example, a blend of the angry and scared expressions is recognized as disgust.
“Also, the method does not deal with blends of emotional expressions.For example, a blend of the angry and scared expressions is recognized as disgust.”
From Automatic analysis of facial expressions: the state of the art (2000) · cites this paper as [2]
Only three of the surveyed systems deal to some extent with rigid head motions.
“Only three of the surveyed systems deal to some extent with rigid head motions ([2], [18], [30]).”
From Automatic analysis of facial expressions: the state of the art (2000) · cites this paper as [2]
The Black and Yacoob method achieved a recognition rate of 88 percent when tested on 70 image sequences containing 145 expressions shown by 40 subjects.
“The achieved recognition rate was 88 percent.”
From Automatic analysis of facial expressions: the state of the art (2000) · cites this paper as [2]
Citations
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Self-citation
Flagged first, then by citations
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Automatic analysis of facial expressions: the state of the art
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Metadata
- Authors
- Black, M. J., & Yacoob, Y.
- Affiliations
- Palo Alto Research Center (US)
- University of Maryland, College Park (US)
- Corresponding author
- Black, Michael J.
- Yacoob, Yaser
- ORCID
- Black, Michael J.
- Venue
- International Journal of Computer Vision
- Published
- 1997-10
- Volume
- 25
- Issue
- 1
- Pages
- 23-48
- ISSN
- 0920-5691 (ISSN-L)
- 1573-1405
- OpenAlex
- W1509031088
- Cited by
- 514
- References
- 34
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 2 · 2023: 11 · 2022: 5 · 2021: 7 · 2020: 12 · 2019: 5 · 2018: 12 · 2017: 14 · 2016: 17 · 2015: 21 · 2014: 19 · 2013: 18 · 2012: 12
- FWCI
- 13.61
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- International Journal of Computer Vision (publishedVersion)
- 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
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
- Keywords
- facial expression recognition, facial motion, affine motion model, non-rigid motion, articulated motion, head movement, motion tracking, image sequences
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