A Fuzzy Reasoning Model for Recognition of Facial Expressions
Un modelo de razonamiento difuso para reconocimiento de expresiones faciales
Oleg Starostenko1, Renan Contreras1, Vicente Alarcón Aquino1, Leticia Flores Pulido1, Jorge Rodríguez Asomoza1, Oleg Sergiyenko2, and Vira Tyrsa3
1 Research Center CENTIA, Department of Computing, Electronics and Mechatronics, Universidad de las Américas, 72820, Puebla, Mexico. E–mail: oleg.starostenko@udlap.mx; renan.contrerasgz@udlap.mx; vicente.alarcon@udlap.mx; leticia.florespo@udlap.mx; jorge.rodriguez@udlap.mx
2 Engineering Institute, Autonomous University of Baja California, Blvd. Benito Juárez, Insurgentes Este, 21280, Mexicali, Baja California, Mexico. E–mail: srgnk@iing.mxl.uabc.mx
]]> 3 Universidad Politécnica de Baja California, Mexicali, Baja California, Mexico. E–mail: vera–tyrsa@yandex.ru
Article received on 11/12/2010.
Accepted 05/04/2011.
Abstract
In this paper we present a fuzzy reasoning model and a designed system for Recognition of Facial Expressions, which can measure and recognize the intensity of basic or non–prototypical emotions. The proposed model operates with encoded facial deformations described in terms of either Ekman's Action Units (AUs) or Facial Animation Parameters (FAPs) of MPEG–4 standard and provides recognition of facial expression using a knowledge base implemented on knowledge acquisition and ontology editor Protégé. It allows modeling of facial features obtained from geometric parameters coded by AUs – FAPs and from a set of rules required for classification of measured expressions. This paper also presents a designed framework for fuzzyfication of input variables of a 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 designed according to developed model has been tested in order to evaluate its capability for detection, indexing, classifying, and interpretation of facial expressions.
Keywords: Facial expression recognition, emotion interpretation, knowledge–based framework, rules–based fuzzy classifier.
Resumen
]]> En este artículo presentamos un sistema de razonamiento difuso capaz de reconocer y medir la intensidad de cualquier expresión facial prototípica o no prototípica. El modelo propuesto utiliza como entrada las deformaciones faciales codificadas ya sea en términos de AUs (Ekman FACS) o FAPs (MPEG–4) y provee reconocimiento de expresiones faciales utilizando una base de conocimiento la cual fue implementada utilizando el sistema de adquisición de conocimiento y editor de ontologías Protégé. Esta base de conocimiento permite, además de la creación de modelos de características faciales obtenidos a partir de parámetros geométricos y codificados en términos de AUs y FAPs, también la definición de las reglas requeridas para la clasificación de las expresiones. En este artículo también se presenta un framework diseñado para codificación de las variables de entrada al clasificador difuso basado en los resultados obtenidos del análisis estadístico de las emociones expresadas en grabaciones de video en base estándar de caras creada por Cohn–Kanade y Pantic. El sistema propuesto fue evaluado con el propósito de analizar su capacidad de detección, indexado, clasificación e interpretación de expresiones faciales.Palabras clave: Reconocimiento de expresiones faciales, la interpretación de la emoción, conocimiento marco, clasificador difuso basado en reglas.
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Acknowledgments
This research is sponsored by Mexican National Council of Science and Technology, CONACyT, Projects: #109115 and #109417.
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