Please use this identifier to cite or link to this item: http://ri.uaemex.mx/handle20.500.11799/39489
Title: Facial Geometry Identification through Fuzzy Patterns with RGBD Sensor
Keywords: Computación;Kinect;RGBD;fuzzy logic;face detection;face segmentation;info:eu-repo/classification/cti/7
Publisher: Instituto Politécnico Nacional
Project: http://www.redalyc.org/revista.oa?id=615 
Description: 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.
URI: http://ri.uaemex.mx/handle20.500.11799/39489
Other Identifiers: http://hdl.handle.net/20.500.11799/39489
Rights: info:eu-repo/semantics/Computación y Sistemas
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-nd/4.0
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