Automatic classification of single facial images
Abstract
We propose a method for automatically classifying facial images based on labeled elastic graph matching, a 2D Gabor wavelet representation, and linear discriminant analysis. Results of tests with three image sets are presented for the classification of sex, "race", and expression. A visual interpretation of the discriminant vectors is provided.
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Recognition of nonprototypic facial expressions is feasible if each neural network output unit is associated with a weight from the interval [0,1], as proposed in [106], [44], [71], [56], instead of being associated with either 0 or 1.
“Recognition of nonprototypic facial expressions is feasible, however, if each neural network output unit is associated with a weight from the interval [0,1], as proposed in [106], [44], [71], [56], instead of being associated with either 0 or 1 (e.g., [42], [107]).”
From Automatic analysis of facial expressions: the state of the art (2000) · cites this paper as [71]
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- Authors
- Lyons, M. J., Budynek, J., & Akamatsu, S.
- Affiliations
- Advanced Telecommunications Research Institute International (JP)
- Eurobio (France) (FR)
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 1999
- Volume
- 21
- Issue
- 12
- Pages
- 1357-1362
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2096044434
- Cited by
- 1,075
- References
- 13
- Citations by year
- 2026: 13 · 2025: 11 · 2024: 17 · 2023: 30 · 2022: 58 · 2021: 43 · 2020: 36 · 2019: 77 · 2018: 61 · 2017: 57 · 2016: 57 · 2015: 60 · 2014: 71 · 2013: 47 · 2012: 69
- FWCI
- 9.40
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Pattern Analysis and Machine Intelligence (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face and Expression Recognition
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
- Keywords
- face classification, elastic graph matching, linear discriminant analysis, sex classification, racial classification, facial expression recognition, discriminant vectors
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