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Data Augmentation-Assisted Makeup-Invariant Face Recognition
المؤلفون المشاركون
Ali, Nouman
Ratyal, Naeem
Sajid, Muhammad
Baig, Mirza Jabbar Aziz
Zafar, Bushra
Dar, Saadat Hanif
Butt, Asif Raza
Shafique, Tamoor
Riaz, Imran
Baig, Shahbaz
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-10، 10ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-12-04
دولة النشر
مصر
عدد الصفحات
10
التخصصات الرئيسية
الملخص EN
Recently, face datasets containing celebrities photos with facial makeup are growing at exponential rates, making their recognition very challenging.
Existing face recognition methods rely on feature extraction and reference reranking to improve the performance.
However face images with facial makeup carry inherent ambiguity due to artificial colors, shading, contouring, and varying skin tones, making recognition task more difficult.
The problem becomes more confound as the makeup alters the bilateral size and symmetry of the certain face components such as eyes and lips affecting the distinctiveness of faces.
The ambiguity becomes even worse when different days bring different facial makeup for celebrities owing to the context of interpersonal situations and current societal makeup trends.
To cope with these artificial effects, we propose to use a deep convolutional neural network (dCNN) using augmented face dataset to extract discriminative features from face images containing synthetic makeup variations.
The augmented dataset containing original face images and those with synthetic make up variations allows dCNN to learn face features in a variety of facial makeup.
We also evaluate the role of partial and full makeup in face images to improve the recognition performance.
The experimental results on two challenging face datasets show that the proposed approach can compete with the state of the art.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Sajid, Muhammad& Ali, Nouman& Dar, Saadat Hanif& Ratyal, Naeem& Butt, Asif Raza& Zafar, Bushra…[et al.]. 2018. Data Augmentation-Assisted Makeup-Invariant Face Recognition. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1206500
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Sajid, Muhammad…[et al.]. Data Augmentation-Assisted Makeup-Invariant Face Recognition. Mathematical Problems in Engineering No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1206500
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Sajid, Muhammad& Ali, Nouman& Dar, Saadat Hanif& Ratyal, Naeem& Butt, Asif Raza& Zafar, Bushra…[et al.]. Data Augmentation-Assisted Makeup-Invariant Face Recognition. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1206500
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1206500
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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