Global and Feature Based Gender Classification of Faces: A Comparison of Human Performance and Computational Models
Buchala, S., Davey, N., Gale, T.M. and Frank, R.
(2005)
Global and Feature Based Gender Classification of Faces: A Comparison of Human Performance and Computational Models.
Proceedings of the Ninth Neural Computation and Psychology Workshop - NCPW, 2004.
pp. 349-360.
Most computational models for gender classification use global information (the full face image) giving equal weight to the whole face area irrespective of the importance of the internal features. Here, we use a global and feature based representation of face images that includes both global and featural information. We use dimensionality reduction techniques and a support vector machine classifier and show that this method performs better than either global or feature based representations alone.
Item Type | Article |
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Additional information | Original paper can be found at: http://eproceedings.worldscinet.com/9789812701886/9789812701886_0036.html Copyright World Scientific Publishing Company. http://dx.doi.org/10.1142/9789812701886_0036 |
Date Deposited | 15 May 2025 11:37 |
Last Modified | 30 May 2025 23:33 |
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