Since facial expressions are a key modality in human communication, the automated analysis of facial images for the estimation of the displayed expression is central in the design of intuitive and human friendly human computer interaction systems. In existing approaches, over-formalised description of knowledge concerning the human face and human expressions, as well as failures of the image and video processing components, often lead to misclassification. In this paper, we propose the utilisation of extended fuzzy rules for the more flexible description of knowledge, and the consideration of uncertainty and lack of confidence in the process of feature extraction from image and video. The two are combined using a flexible possibilistic rule evaluation structure, leading to more robust overall operation. The proposed approach has been implemented as an extension to an existing expression analysis system and conclusions from comparative study have been drawn.
['Manolis Wallace', 'Spiros Ioannou', 'Amaryllis Raouzaiou', 'Kostas Karpouzis', 'Stefanos D. Kollias']
Dealing with feature uncertainty in facial expression recognition