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Computer‐Suggested Facial Makeup
Author(s) -
Scherbaum Kristina,
Ritschel Tobias,
Hullin Matthias,
Thormählen Thorsten,
Blanz Volker,
Seidel HansPeter
Publication year - 2011
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/j.1467-8659.2011.01874.x
Subject(s) - computer science , artificial intelligence , exaggeration , computer vision , face (sociological concept) , specularity , representation (politics) , task (project management) , active appearance model , reflectivity , computer graphics (images) , image (mathematics) , psychology , social science , physics , management , optics , quantum mechanics , psychiatry , sociology , politics , political science , law , economics , specular reflection
Finding the best makeup for a given human face is an art in its own right. Experienced makeup artists train for years to be skilled enough to propose a best‐fit makeup for an individual. In this work we propose a system that automates this task. We acquired the appearance of 56 human faces, both without and with professional makeup. To this end, we use a controlled‐light setup, which allows to capture detailed facial appearance information, such as diffuse reflectance, normals, subsurface‐scattering, specularity, or glossiness. A 3D morphable face model is used to obtain 3D positional information and to register all faces into a common parameterization. We then define makeup to be the change of facial appearance and use the acquired database to find a mapping from the space of human facial appearance to makeup. Our main application is to use this mapping to suggest the best‐fit makeup for novel faces that are not in the database. Further applications are makeup transfer, automatic rating of makeup, makeup‐training, or makeup‐exaggeration. As our makeup representation captures a change in reflectance and scattering, it allows us to synthesize faces with makeup in novel 3D views and novel lighting with high realism. The effectiveness of our approach is further validated in a user‐study.