Abstract
Facial expression recognition is an important application in computer vision. Generally, features which are used for facial expression recognition are mostly based on geometric and appearance features of image. This paper presents a novel method to identify facial expressions which exploring eye movements data labels as auxiliary labels to construct classifier, a Strengthened Deep Belief Network (SDBN) in a united cycle framework is constructed. This framework is formed as strong classifier by multi-weak classifiers voted. Experiments on Cohn-Kanade database showed that the proposed method achieved a better improvement in the task of facial expression recognition.
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