Facial emotional classification: from a discrete perspective to a continuous emotional space
Pattern Analysis and Applications, 2013•Springer
User emotion detection is a very useful input to develop affective computing strategies in
modern human computer interaction. In this paper, an effective system for facial emotional
classification is described. The main distinguishing feature of our work is that the system
does not simply provide a classification in terms of a set of discrete emotional labels, but that
it operates in a continuous 2D emotional space enabling a wide range of intermediary
emotional states to be obtained. As output, an expressional face is represented as a point in …
modern human computer interaction. In this paper, an effective system for facial emotional
classification is described. The main distinguishing feature of our work is that the system
does not simply provide a classification in terms of a set of discrete emotional labels, but that
it operates in a continuous 2D emotional space enabling a wide range of intermediary
emotional states to be obtained. As output, an expressional face is represented as a point in …
Abstract
User emotion detection is a very useful input to develop affective computing strategies in modern human computer interaction. In this paper, an effective system for facial emotional classification is described. The main distinguishing feature of our work is that the system does not simply provide a classification in terms of a set of discrete emotional labels, but that it operates in a continuous 2D emotional space enabling a wide range of intermediary emotional states to be obtained. As output, an expressional face is represented as a point in a 2D space characterized by evaluation and activation factors. The classification method is based on a novel combination of five classifiers and takes into consideration human assessment for the evaluation of the results. The system has been tested with an extensive universal database so that it is capable of analyzing any subject, male or female of any age and ethnicity. The results are very encouraging and show that our classification strategy is consistent with human brain emotional classification mechanisms.
Springer
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