Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/40333
Title: Soft biometric attributes in the wild: case study on gender classification
Authors: Castrillón-Santana, Modesto 
Lorenzo Navarro, José Javier 
UNESCO Clasification: 120304 Inteligencia artificial
Keywords: Face Recognition
Fusion
Identification
Surveillance
Prediction
Features
Images
Age
Issue Date: 2017
Abstract: 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
Source: Human Recognition in Unconstrained Environments, Chapter 7. Academic Press, p. 145-176, ISBN 9780081007051
Appears in Collections:Artículos
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