| Revue: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560471 |
| ISSN: | 1405-5546 |
| Autores: | Mansouri, Nabila1 |
| Instituciones: | 1Ha’il University, Hail. Arabia Saudita |
| Año: | 2020 |
| Periodo: | Abr-Jun |
| Volumen: | 24 |
| Número: | 2 |
| Paginación: | 883-895 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Resumen en inglés | Aging is non-reversible process. Human face and gait change with time which reflects major variations in appearance, the vast majority of people are able to easily recognize human traits like emotional states, where they can tell if the person is happy, sad or angry from the face, likewise, it is easy to determine the gender of the person. However, knowing person’s age is a very challenge task. Hence, significant interest in the computer vision and pattern recognition research community is given to automatic age estimation. This paper, presents a thorough analysis of recent research in aging and age estimation. We discuss popular algorithms used in age estimation and existing models. Underline age estimation challenges especially using RGB images. Finally insights for future research based on depth map and Kinect camera. |
| Disciplinas: | Ciencias de la computación |
| Palabras clave: | Inteligencia artificial |
| Keyword: | Age estimation, Face aging, Gait, Survey, RGB-D, Depth map, Artificial intelligence |
| Texte intégral: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
