A reduced region of interest based approach for facial expression recognition from static images

摘要

The general approach to facial expression recognition involves three stages: face acquisition, feature extraction and expression recognition. A series of steps are used during feature extraction, and the robustness of a recognition model depends on the ability to handle exceptions over all these steps. This paper details experiments conducted to classify images by facial expression using reduced regions of interest and discriminative salient patches on the face, while minimizing the number of steps required for their localization. The performance of various feature descriptors is analyzed and a model for expression recognition for which experiments on the JAFFE database show effectiveness is proposed.