Análisis y Comparación del Descriptor Cone Curvature frente al Reconocimiento de Expresiones Faciales

Analysis and Comparison of the Cone Curvature Descriptor in Facial Gesture Recognition Tasks

  • Julián Severiano Rodriguez Acevedo Universidad de San Buenaventura Bogotá
  • Flavio Augusto Prieto Ortiz Universidad Nacional de Colombia
Palabras clave: Artificial vision, facial recognized, shape descriptors (en_US)
Palabras clave: Descriptores de forma, reconocimiento facial, Visión artificial (es_ES)

Resumen (es_ES)

Se presenta el resultado de analizar el comportamiento del descriptor de forma Cone Curvature (CC) en la tarea de reconocimiento de expresiones faciales en imágenes 3D. El descriptor CC es una representación del modelo 3D que se calcula a partir de un conjunto de ondas de modelado para cada vértice de una malla poligonal. Se empleó la base de datos de rostros 3D (BU-3DFE), la cual contiene imágenes con 6 expresiones faciales. Con el uso del descriptor CC, las expresiones fueron reconocidas en un porcentaje promedio del 76.67% con una red neuronal, y del 78.88% con un clasificador bayesiano. Al realizar una combinación del descriptor CC con otros descriptores como DESIRE y Spherical Spin Image, se logr´o un porcentaje promedio de reconocimiento de gestos del 90.27% y del 97.2 %, usando los mismos clasificadores mencionados previamente.

Resumen (en_US)

This article presents the results of analyzing the behavior of the Cone Curvature shape
descriptor (CC) in the task of recognition of facial expressions in 3D images. The CC
descriptor is a representation of the 3D model computed from a set of waves modeling
for each vertex of a polygon mesh. The 3D Facial Expression Database (BU-3DFE) was
used, which contains images with six facial expressions. With the use of the CC descriptor,
the expressions were recognized in an average percentage of 76.67% with a neural
network, and of 78.88% with a Bayesian classifier. By combining the CC descriptor with
other descriptors such as DESIRE and Spherical Spin Image, it was achieved an average
percentage of gesture recognition of 90.27%and 97.2 %, using the mentioned classifiers.

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Biografía del autor/a

Julián Severiano Rodriguez Acevedo, Universidad de San Buenaventura Bogotá
Profesor Asociado Facultad de Ingeniería
Flavio Augusto Prieto Ortiz, Universidad Nacional de Colombia
Profesor Asociado Facultad de Ingeniería Universidad Nacional de Colombia

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Cómo citar
Rodriguez Acevedo, J. S., & Prieto Ortiz, F. A. (2015). Análisis y Comparación del Descriptor Cone Curvature frente al Reconocimiento de Expresiones Faciales. Ingeniería, 20(2), 271-285. https://doi.org/10.14483/23448393.8620
Publicado: 2015-08-31