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

De Sousa, R. J. R.; Rodrigues, J. M. F.; du Buf, J. M. H.

http://hdl.handle.net/10400.1/6979

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Authors

De Sousa, R. J. R.

Rodrigues, J. M. F.

du Buf, J. M. H.

Abstract(s)

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%.