Emotional Expression Recognition using Support Vector Machines
Melanie Dumas · 2001
The objective of this paper is to apply Support Vector Machines to the problem of classifying emotion on images of human faces. This welldefined problem is complicated by the natural variation in people's faces, requiring the classification algorithm to distinguish the small number of relevant features from the large pool of input features. Recent experimentation using neural networks has achieved over 85% classification accuracy. These experiments provide a metric for evaluation of the Support Vector Machine technique, which was shown to have equivalent performance to neural networks. 1