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Facial makeup detection technique based on texture and shape analysis

  • Eurecom
  • CNRS LTCI

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publication2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479960262
DOIs
Publication statusPublished - 17 Jul 2015
Externally publishedYes
Event11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015 - Ljubljana, Slovenia
Duration: 4 May 20158 May 2015

Publication series

Name2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015

Conference

Conference11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015
Country/TerritorySlovenia
CityLjubljana
Period4/05/158/05/15

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