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Facial emotional classification: from a discrete perspective to a continuous emotional space


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.

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This work has been partly financed by the Spanish Government through the DGICYT contract TIN2011-24660, by the project FEDER ATIC, and the SISTRONIC Group of the Aragon Institute of Technology (Ref. T84).

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Correspondence to Isabelle Hupont.

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Hupont, I., Baldassarri, S. & Cerezo, E. Facial emotional classification: from a discrete perspective to a continuous emotional space. Pattern Anal Applic 16, 41–54 (2013).

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  • Affective computing
  • Algorithms
  • Facial expression analysis
  • Intelligent user interfaces