Facial ethnic appearance synthesis

Abstract

In this work, we have explored several subspace reconstruction methods for facial ethnic appearance synthesis (FEAS). In our experiments, our proposed dual subspace modeling using the Fukunaga Koontz transform (FKT) yields much better facial ethnic synthesis results than the ℓ 1 minimization, the ℓ 2 minimization and the principal component analysis (PCA) reconstruction method. With that, we are able to automatically and efficiently synthesize different facial ethnic appearance and alter the facial ethnic appearance of the query image to any other ethnic appearance as desired. Our technique well preserves the facial structure of the query image and simultaneously synthesize the skin tone and ethnic features that best matches target ethnicity group. Facial ethnic appearance synthesis can be applied to synthesizing facial images of a particular ethnicity group for unbalanced database, and can be used to train ethnicity invariant classifiers by generating multiple ethnic appearances of the same subject in the training stage.