Confidence-Based Fusion of Multiple Feature Cues for Facial Expression Recognition
Since facial expressions are a key modality in human communication, the automated analysis of facial images for the estimation of the displayed expression is essential in the design of intuitive and accessible human computer interaction systems. In most existing rule-based expression recognition approaches, analysis is semiautomatic or requires high quality video. In this paper we propose a feature extraction system which combines analysis from multiple channels based on their confidence, to result in better facial feature boundary detection. The facial features are then used for expression estimation. The proposed approach has been implemented as an extension to an existing expression analysis system in the framework of the IST ERMIS project