Recognition of Facial Expressions by Cortical Multi-scale Line and Edge Coding

Abstract. Face-to-face communications between humans involve emotions, which often are unconsciously conveyed by facial expressions and body gestures. Intelligent human-machine interfaces, for example in cognitive robotics, need to recognize emotions. This paper addresses facial expressions and their neural correlates on the basis of a model of the visual cortex: the multi-scale line and edge coding. The recognition model links the cortical representation with Paul Ekman’s Action Units which are related to the different facial muscles. The model applies a top-down categorization with trends and magnitudes of displacements of the mouth and eyebrows based on expected displacements relative to a neutral expression. The happy vs. not-happy categorization yielded a correct recognition rate of 91%, whereas final recognition of the six expressions happy, anger, disgust, fear, sadness and surprise resulted in a rate of 78%.

• Type: Journal
• Year: 2010
• Where: ICIAR
• Authors: R. J. R. de Sousa, J. M. F. Rodrigues, J. M. Hans du Buf
• Keywords: Different Facial Muscles, Facial Expressions, ICIAR 2010, Image Analysis, Intelligent Human-machine Interfaces