A Fuzzy Reasoning Model for Recognition of Facial Expressions
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...
| Autores: | , , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2011 |
| País: | México |
| Institución: | Universidad de las Américas Puebla |
| Repositorio: | Redalyc-UDLAP |
| OAI Identifier: | oai:redalyc.org:61520938004 |
| Acceso en línea: | https://www.redalyc.org/articulo.oa?id=61520938004 |
| Access Level: | acceso abierto |
| Palabra clave: | Computación rules knowledge based framework emotion interpretation based fuzzy classifier |
| Sumario: | 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. |
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