Título

Facial Geometry Identification through Fuzzy Patterns with RGBD Sensor

Autor

VICTOR FERNANDEZ CERVANTES

ARTURO GARCIA ROMERO

Marco Antonio Ramos Corchado

ANDRES MENDEZ VAZQUEZ

Nivel de Acceso

true

Acceso Abierto

Resumen o descripción

Automatic human facial recognition is an important and complicated task; it is necessary to design algorithms capable of recognizing the constant patterns in the face and to use computing resources efficiently. In this paper we present a novel algorithm to recognize the human face in real time; the systems input is the depth and color data from the Microsoft KinectTM device. The algorithm recognizes patterns/shapes on the point cloud topography. The template of the face is based in facial geometry; the forensic theory classifies the human face with respect to constant patterns: cephalometric points, lines, and areas of the face. The topography, relative position, and symmetry are directly related to the craniometric points. The similarity between a point cloud cluster and a pattern description is measured by a fuzzy pattern theory algorithm. The face identification is composed by two phases: the first phase calculates the face pattern hypothesis of the facial points, configures each point shape, the related location in the areas, and lines of the face. Then, in the second phase, the algorithm performs a search on these face point configurations.

Editor

Instituto Politécnico Nacional

Fecha de publicación

2015

Tipo de publicación

Artículo

Formato

application/application/pdf

Fuente

Computación y Sistemas (México) Num.3 Vol.19

Idioma

Inglés

Relación

http://www.redalyc.org/revista.oa?id=615

Audiencia

Estudiantes

Investigadores

Repositorio Orígen

REPOSITORIO INSTITUCIONAL DE LA UAEM

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