Multi-scale score level fusion of local descriptors for gender classification in the wild
Data(s) |
12/07/2016
12/07/2016
2016
|
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Resumo |
<p>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...</p> |
Identificador |
http://hdl.handle.net/10553/17812 726315 <p><a href="http://dx.doi.org/10.1007/s11042-016-3653-2" target="_blank">10.1007/s11042-016-3653-2</a></p> |
Idioma(s) |
eng |
Direitos |
info:eu-repo/semantics/openAccess |
Fonte |
<p>Multimedia Tools and Applications. ISSN 1380-7501. ISSN online 1573-7721</p> |
Palavras-Chave | #1203 Ciencia de los ordenadores |
Tipo |
info:eu-repo/semantics/article |