Face and gesture recognition by using a relevance analysis with 3D images

The 3D face recognition aims to reduce the flaws that present the bi-dimensional based methods. This kind of recognizing method has the advantage to be invariant to illumination changes because the faces are represented as a points cloud or a 3D mesh where the most remarkable is the geometry. In this research work we present a recognizing system that uses a set of 3D shape descriptors that were selected from a relevance analysis by using the Fisher coefficients in different regions of face which are part of an anthropometric face model. A set of experiments for face, expression, and gender recognition and were performed using the relevance analysis proposed. The obtained results show that the relevance analysis offers an increasing of the performance in face recognition system. 

• Tipo de recurso: http://purl.org/coar/resource_type/c_6524
• Fecha de publicación: 2013
• Institución: Universidad Pedagógica y Tecnológica de Colombia
• Repositorio: RiUPTC: Repositorio Institucional UPTC
• Idioma: spa
• OAI Identifier: oai:repositorio.uptc.edu.co:001/10181
• Acceso en línea: https://revistas.uptc.edu.co/index.php/investigacion_duitama/article/view/2563; https://repositorio.uptc.edu.co/handle/001/10181
• Palabra clave: 3D face recognition; 3D segmentation; 3D shape descriptor; machine learning; relevance analysis.; análisis de relevancia; aprendizaje de máquina; descriptores de forma 3D; reconocimiento de rostros 3D; segmentación 3D.
• License: Derechos de autor 2013 REVISTA DE INVESTIGACIÓN DESARROLLO E INNOVACIÓN