Recognizing facial expressions by spatio-temporal analysis
Abstract
An approach for analysis and representation of facial dynamics for recognition of facial expressions from image sequences is proposed. The algorithms the authors develop utilize optical flow computation to identify the direction of rigid and non-rigid motions that are caused by human facial expressions. A mid-level symbolic representation that is motivated by linguistic and psychological considerations is developed. Recognizing six facial expressions, as well as eye blinking, are demonstrated on a collection of image sequences.
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The utilized techniques include holistic spatial analysis, spatio-temporal analysis, and analytic spatial analysis.
“The utilized techniques include holistic spatial analysis [13], [70], [54], spatio-temporal analysis [52], [100], [73], [57], and analytic spatial analysis [93], [43], [44], [92], [40].”
From Automatic analysis of facial expressions: the state of the art (2000) · cites this paper as [70]
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References 5 · Cited by 34
- Authors
- Yaccob, Y., & Davis, L.
- Affiliations
- University of Maryland, College Park (US)
- ORCID
- Davis, L.
- Venue
- Proceedings of 12th International Conference on Pattern Recognition
- Publisher
- IEEE Comput. Soc. Press
- Published
- 2002-12-17
- Volume
- 1
- Pages
- 747-749
- ISSN
- 1041-3278 (ISSN-L)
- OpenAlex
- W2158044368
- Cited by
- 34
- References
- 5
- Citations by year
- 2026: 1 · 2024: 1 · 2021: 1 · 2017: 1 · 2016: 1 · 2014: 1
- FWCI
- 2.41
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition (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
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
- Keywords
- facial expression recognition, facial dynamics, optical flow, spatio-temporal analysis, non-rigid motion, rigid body motion, blinking, image sequences
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