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http://hdl.handle.net/10553/17812
Título: | Multi-scale score level fusion of local descriptors for gender classification in the wild | Autores/as: | Castrillón-Santana, Modesto Lorenzo Navarro, José Javier Ramón Balmaseda, Enrique José |
Clasificación UNESCO: | 120304 Inteligencia artificial | Palabras clave: | Soft biometrics Gender classification Local descriptors Score level fusion CNN |
Fecha de publicación: | 2017 | Publicación seriada: | Multimedia Tools and Applications | Resumen: | The 2015 FRVT gender classification (GC) report evidences the problems that current approaches tackle in situations with large variations in pose, illumination, background and facial expression. The report suggests that both commercial and research solutions are hardly able to reach an accuracy over 90% for The Images of Groups dataset, a proven scenario exhibiting unrestricted or in the wild conditions. In this paper, we focus on this challenging dataset, stepping forward in GC performance by observing: 1) recent literature results combining multiple local descriptors, and 2) the psychophysics evidences of the greater importance of the ocular and mouth areas to solve this task... | URI: | http://hdl.handle.net/10553/17812 | ISSN: | 1380-7501 | DOI: | 10.1007/s11042-016-3653-2 | Fuente: | Multimedia Tools and Applications [ISSN 1380-7501], v. 76 (4), p. 4695–4711 |
Colección: | Artículos |
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