[ Análisis de estudio de casos para estimar la edad basado en detección de rostros en las imágenes digitales ]
Volume 25, Issue 1, June 2016, Pages 130–140
Luis Enrique Colmenares-Guillen1, Francisco Javier Albores Velasco2, and Omar Gonzalo Ledo Moreno3
1 Facultad de Ciencias de la Computación, Benemérita Universidad Autónoma de Puebla, Mexico
2 Facultad de Ingeniería y Tecnología, Universidad Autónoma de Tlaxcala, Mexico
3 Facultad de Ciencias de la Computación, Benemérita Universidad Autónoma de Puebla, mexico
Original language: Spanish
Copyright © 2016 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Age estimation based on face detection, is one of the different areas of study within digital images and is widely used by researchers and the by the different technological applications. Consequently, the present research focuses on studying the methods and the most important trends on age classification based on different analyzes of the main facial characteristics of a person such as the proportions of the face, identifying wrinkles, drooping eyelids, and fiducial points, among others. With these data, and using computational learning algorithms, better known as support vector machines and artificial neural networks, an analysis of some classification processes it is performed. Some age estimators such as OpenBR and Face API were also tried in order to obtain solutions that help generate new proposals for age estimation. Determining the age of people can be of assistance for marketing studies; for selecting contents suitable to certain age groups; for systems based on human interactions; and the probable detection of child pornography, which help to prevent criminal content subsisting on the web.
Author Keywords: Age estimation, face detection, anthropometric model, age classification, human faces.
Volume 25, Issue 1, June 2016, Pages 130–140
Luis Enrique Colmenares-Guillen1, Francisco Javier Albores Velasco2, and Omar Gonzalo Ledo Moreno3
1 Facultad de Ciencias de la Computación, Benemérita Universidad Autónoma de Puebla, Mexico
2 Facultad de Ingeniería y Tecnología, Universidad Autónoma de Tlaxcala, Mexico
3 Facultad de Ciencias de la Computación, Benemérita Universidad Autónoma de Puebla, mexico
Original language: Spanish
Copyright © 2016 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Age estimation based on face detection, is one of the different areas of study within digital images and is widely used by researchers and the by the different technological applications. Consequently, the present research focuses on studying the methods and the most important trends on age classification based on different analyzes of the main facial characteristics of a person such as the proportions of the face, identifying wrinkles, drooping eyelids, and fiducial points, among others. With these data, and using computational learning algorithms, better known as support vector machines and artificial neural networks, an analysis of some classification processes it is performed. Some age estimators such as OpenBR and Face API were also tried in order to obtain solutions that help generate new proposals for age estimation. Determining the age of people can be of assistance for marketing studies; for selecting contents suitable to certain age groups; for systems based on human interactions; and the probable detection of child pornography, which help to prevent criminal content subsisting on the web.
Author Keywords: Age estimation, face detection, anthropometric model, age classification, human faces.
Abstract: (spanish)
La estimación de edad, basado en rostros es una de las diferentes áreas de estudio dentro de las imágenes digitales y que es ampliamente utilizado por investigadores y por las distintas aplicaciones tecnológicas. Por consiguiente, el presente trabajo de investigación se enfoca a estudiar los métodos y tendencias más importantes de clasificación de edad basado en diferentes análisis de características principales faciales de una persona como pueden ser: las proporciones de la cara, identificación de arrugas, caída de parpados, puntos fiduciales, entre otros. Con estos datos, se lleva a cabo el análisis de algunos procesos de clasificación, utilizando algoritmos de aprendizaje computacional mejor conocidos como máquinas de soporte vectorial y redes neuronales artificiales. También, se efectuaron, algunas pruebas de los estimadores de edad, como OpenBR y Face API, para obtener soluciones que ayuden a generar nuevas propuestas para estimar la edad. Determinar la edad de las personas puede transformarse en una gran ayuda, para estudios de mercadeo, para la selección de contenidos aptos para ciertos grupos etarios, para sistemas que se basan en interacciones humanas y para posible detección de pornografía infantil que ayude a prevenir contenidos delictivos que existen en la web.
Author Keywords: Estimación de edad, detección de rostros, modelo antropométrico, clasificación edad, rostros humanos.
How to Cite this Article
Luis Enrique Colmenares-Guillen, Francisco Javier Albores Velasco, and Omar Gonzalo Ledo Moreno, “Case study analysis to estimate the age based on face detection digital images,” International Journal of Innovation and Scientific Research, vol. 25, no. 1, pp. 130–140, June 2016.
