FG 2015, 11th IEEE International Conference on Automatic Face and Gesture Recognition, May 4-8, 2015, Ljubljana, Slovenia
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.
Type:
Conférence
City:
Ljubljana
Date:
2015-05-04
Department:
Sécurité numérique
Eurecom Ref:
4494
Copyright:
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