Facial Geometry Identification through Fuzzy Patterns with RGBD Sensor
Víctor Fernández-Cervantes1, Arturo García1, Marco Antonio Ramos2, Andrés Méndez1
1 Instituto Politécnico Nacional, CINVESTAV, Guadalajara, México. vfernand@gdl.cinvestav.mx, aggarcia@gdl.cinvestav.mx, amendez@gdl.cinvestav.mx
2 Universidad Autónoma del Estado de México, México. mramos@univ-tlse1.fr
Corresponding author is Víctor Fernández Cervantes.
]]> Article received on 24/11/2014.
Abstract
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 system's 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.
Keywords: Kinect, RGBD, fuzzy logic, face detection, face segmentation.
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Acknowledgements
]]> This work has been funded by CONACYT scholarship number 212753. The authors want to thank Víctor Rodríguez, Isela Ayar, Juan Manuel Rodríguez, Emily "Godzilla" Marlen Rodríguez, Stuart and Maria Embleton who participated in the project.
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