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Facial Feature Model for Emotion Recognition Using Fuzzy Reasoning

  • Renan Contreras
  • Oleg Starostenko
  • Vicente Alarcon-Aquino
  • Leticia Flores-Pulido
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6256)

Abstract

In this paper we present a fuzzy reasoning system that can measure and recognize the intensity of basic or non-prototypical facial expressions. The system inputs are the encoded facial deformations described either in terms of Ekman´s Action Units (AUs) or Facial Animation Parameters (FAPs) of MPEG-4 standard. The proposed fuzzy system uses a knowledge base implemented on knowledge acquisition and ontology editor Protégé. It allows the modeling of facial features obtained from geometric parameters coded by AUs - FAPs and also the definition of rules required for classification of measured expressions. This paper also presents the designed framework for fuzzyfication of input variables for fuzzy classifier based on statistical analysis of emotions expressed in video records of standard Cohn-Kanade’s and Pantic´s MMI face databases. The proposed system has been tested in order to evaluate its capability for detection, classifying, and interpretation of facial expressions.

Keywords

Emotion recognition facial features knowledge-based framework rules-based fuzzy classifier 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Renan Contreras
    • 1
  • Oleg Starostenko
    • 1
  • Vicente Alarcon-Aquino
    • 1
  • Leticia Flores-Pulido
    • 1
  1. 1.CENTIA, Department of Computing, Electronics and MechatronicsUniversidad de las AméricasPueblaMéxico

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