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%. © 2010 Springer-Verlag.
CITATION STYLE
De Sousa, R. J. R., Rodrigues, J. M. F., & Du Buf, J. M. H. (2010). Recognition of facial expressions by cortical multi-scale line and edge coding. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6111 LNCS, pp. 415–424). https://doi.org/10.1007/978-3-642-13772-3_42
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