Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/40333
Título: | Soft biometric attributes in the wild: case study on gender classification | Autores/as: | Castrillón-Santana, Modesto Lorenzo Navarro, José Javier |
Clasificación UNESCO: | 120304 Inteligencia artificial | Palabras clave: | Face Recognition Fusion Identification Surveillance Prediction, et al. |
Fecha de publicación: | 2017 | Resumen: | Soft biometrics has become an active field of research, as it provides useful attributes to assist in recognition systems. Its fusion with strong traits may serve to achieve reasonable recognition rates in less cooperative scenarios. These attributes can also be used to speed up database searches, or to describe an anonymous subject within a demographic group. Agreeing with recent research trends on the need to evaluate biometric systems using “in the wild” datasets, the current state-of-the-art in the emerging field of soft biometrics is presented, together with proposals and results on the particular problem of gender classification “in the wild”. | URI: | http://hdl.handle.net/10553/40333 | ISSN: | 9780081007051 | DOI: | 10.1016/B978-0-08-100705-1.00007-5 | Fuente: | Human Recognition in Unconstrained Environments, Chapter 7. Academic Press, p. 145-176, ISBN 9780081007051 |
Colección: | Artículos |
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