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Facial makeup detection technique based on texture and shape analysis

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Résumé

Recent studies show that the performances of face recognition systems degrade in presence of makeup on face. In this paper, a facial makeup detector is proposed to further reduce the impact of makeup in face recognition. The performance of the proposed technique is tested using three publicly available facial makeup databases. The proposed technique extracts a feature vector that captures the shape and texture characteristics of the input face. After feature extraction, two types of classifiers (i.e. SVM and Alligator) are applied for comparison purposes. In this study, we observed that both classifiers provide significant makeup detection accuracy. There are only few studies regarding facial makeup detection in the state-of-the art. The proposed technique is novel and outperforms the state-of-the art significantly.

langue originaleAnglais
titre2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015
EditeurInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronique)9781479960262
Les DOIs
étatPublié - 17 juil. 2015
Modification externeOui
Evénement11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015 - Ljubljana, Slovénie
Durée: 4 mai 20158 mai 2015

Série de publications

Nom2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015

Une conférence

Une conférence11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015
Pays/TerritoireSlovénie
La villeLjubljana
période4/05/158/05/15

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