Comparison between geometry-based and Gabor-wavelets-based facial expression recognition using multi-layer perceptron
Abstract
The authors investigate the use of two types of features extracted from face images for recognizing facial expressions. The first type is the geometric positions of a set of fiducial points on a face. The second type is a set of multi-scale and multi-orientation Gabor wavelet coefficients extracted from the face image at the fiducial points. They can be used either independently or jointly. The architecture developed is based on a two-layer perceptron. The recognition performance with different types of features has been compared, which shows that Gabor wavelet coefficients are much more powerful than geometric positions. Furthermore, since the first layer of the perceptron actually performs a nonlinear reduction of the dimensionality of the feature space, they have also studied the desired number of hidden units, i.e., the appropriate dimension to represent a facial expression in order to achieve a good recognition rate. It turns out that five to seven hidden units are probably enough to represent the space of feature expressions.
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Some methods listed in Table 2 do not perform automatic facial data extraction; others achieve this by using facial motion analysis.
“Some of the methods listed in Table 2 do not perform automatic facial data extraction (see column 8); the others achieve this by using facial motion analysis [52], [100], [101], [73], [57].”
From Automatic analysis of facial expressions: the state of the art (2000) · cites this paper as [101]
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- Authors
- Zhang, Z., Lyons, M., Schuster, M., & Akamatsu, S.
- Affiliations
- Institut national de recherche en sciences et technologies du numérique (FR)
- Advanced Telecommunications Research Institute International (JP)
- Venue
- Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition
- Publisher
- IEEE Comput. Soc
- Published
- 2002-11-27
- Pages
- 454-459
- ISSN
- 1541-5058 (ISSN-L)
- OpenAlex
- W2109774206
- Cited by
- 613
- References
- 22
- Citations by year
- 2026: 4 · 2025: 9 · 2024: 10 · 2023: 15 · 2022: 14 · 2021: 29 · 2020: 32 · 2019: 32 · 2018: 32 · 2017: 37 · 2016: 27 · 2015: 41 · 2014: 37 · 2013: 38 · 2012: 26
- FWCI
- 11.25
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Automatic Face and Gesture Recognition (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face and Expression Recognition
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
- Keywords
- facial expression recognition, Gabor wavelets, fiducial points, feature extraction, multilayer perceptron, dimensionality reduction, feature space representation
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