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Title: | MEG: Multi-Expert Gender classification from face images in a demographics-balanced dataset | Authors: | Castrillón-Santana, Modesto De Marsico, Maria Nappi, Michele Riccio, Daniel |
UNESCO Clasification: | 120304 Inteligencia artificial | Keywords: | Recognition | Issue Date: | 2015 | Publisher: | Springer | Journal: | Lecture Notes in Computer Science | Conference: | 18th International Conference on Image Analysis and Processing (ICIAP 2015) | Abstract: | In this paper we focus on gender classification from face images, which is still a challenging task in unrestricted scenarios. This task can be useful in a number of ways, e.g., as a preliminary step in biometric identity recognition supported by demographic information.We compare a feature based approach with two score based ones. In the former, we stack a number of feature vectors obtained by different operators, and train a SVM based on them. In the latter, we separately compute the individual scores from the same operators, then either we feed them to a SVM, or exploit likelihood ratio based on a pairwise comparison of their answers. | URI: | http://hdl.handle.net/10553/20097 | ISBN: | 978-3-319-23230-0 | ISSN: | 0302-9743 | DOI: | 10.1007/978-3-319-23231-7_2 | Source: | Image Analysis and Processing — ICIAP 2015. ICIAP 2015. Lecture Notes in Computer Science, v. 9279 LNCS, p. 15-26 |
Appears in Collections: | Capítulo de libro |
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