YouTube Makeup Dataset (YMU)

Available for download here.

A face image dataset obtained from YouTube makeup tutorials. The images are captured both before and after the makeup application. The dataset consists of 151 white, female subjects with a minimum of 4 images per subject (2 before-makeup images and 2 after-makeup images). Some subjects have 6 images (3 before-makeup images and 3 after-makeup images). The amount of makeup a subject applies to their face varies from subtle to heavy. The cosmetic alteration is primarily applied to the ocular area; the ocular areas are modified using diverse set of eye makeup products. The skin appearance is also changed due to the application of foundation and lip stick/gloss. In some cases, the hair style changes drastically between the before and after makeup images. The dataset also include expression and pose variations.

C. Chen, A. Dantcheva, A. Ross, "Automatic Facial Makeup Detection with Application in Face Recognition," Proc. of 6th IAPR International Conference on Biometrics (ICB), (Madrid, Spain), June 2013.

A. Dantcheva, C. Chen, A. Ross, "Can Facial Cosmetics Affect the Matching Accuracy of Face Recognition Systems?," Proc. of 5th IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS), (Washington DC, USA), September 2012.