". Gender categorization, based on the analysis of facial appearance, can be useful in a large set of applications. In this paper we investigate the gender classification problem from a non-conventional perspective. In particular, the analysis will aim to determine the factors critically affecting the accuracy of available technologies, better explaining differences between face-based identification and gender categorization.. . A novel challenging protocol is proposed, exploiting the dimensions of the Face Recognition Grand Challenge version 2.0 database (FRGC2.0). This protocol is evaluated against several classification algorithms and different kind of features, such as Gabor and LBP. The results obtained show that gender classification can be made independent from other appearance-based factors such as the skin color, facial expression, and illumination condition.. Computer Vision – ECCV 2012. Workshops and Demonstrations Computer Vision – ECCV 2012. Workshops and Demonstrations Look. Inside. . Other actions. . Export citation. About this Book. Reprints and Permissions. Add to Papers. . Share. Share this content on Facebook Share this content on Twitter Share this content on LinkedIn"
Understanding critical factors in appearance-based gender categorization / Grosso, Enrico; Lagorio, Andrea; Pulina, Luca; Tistarelli, Massimo. - 7584:(2012), pp. 280-289. (Intervento presentato al convegno 12th European Conference on Computer Vision, ECCV 2012 tenutosi a Florence, Italy nel October 7-13 2012) [10.1007/978-3-642-33868-7_28].
Understanding critical factors in appearance-based gender categorization
GROSSO, Enrico;LAGORIO, Andrea;PULINA, Luca;TISTARELLI, Massimo
2012-01-01
Abstract
". Gender categorization, based on the analysis of facial appearance, can be useful in a large set of applications. In this paper we investigate the gender classification problem from a non-conventional perspective. In particular, the analysis will aim to determine the factors critically affecting the accuracy of available technologies, better explaining differences between face-based identification and gender categorization.. . A novel challenging protocol is proposed, exploiting the dimensions of the Face Recognition Grand Challenge version 2.0 database (FRGC2.0). This protocol is evaluated against several classification algorithms and different kind of features, such as Gabor and LBP. The results obtained show that gender classification can be made independent from other appearance-based factors such as the skin color, facial expression, and illumination condition.. Computer Vision – ECCV 2012. Workshops and Demonstrations Computer Vision – ECCV 2012. Workshops and Demonstrations Look. Inside. . Other actions. . Export citation. About this Book. Reprints and Permissions. Add to Papers. . Share. Share this content on Facebook Share this content on Twitter Share this content on LinkedIn"I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
