Genealogical face recognition based on UB KinFace database

In this paper, we consider a challenging problem raised in biometric recently, genealogical face recognition. Practically, kinship can be proved via several methods, i.e., gene match. We argue in this paper that merely based on facial appearance can we present an accepted result on kinship verification, though there is remarkable appearance variance between kinship members. Essentially, as an extension of our former study, we proceed with the following work. First, an extended kinship database named “UB KinFace Ver2.0” is introduced. Second, we propose to use robust local Gabor filters to extract genetic-invariant features. Finally, metric learning and transfer subspace learning are adopted to abridge the great discrepancy between children and their old parents. The key idea is to take advantage of some intermediate data, e.g. young parents, close to both source and target data. Experimental results demonstrate the effectiveness of our kinship verification methods.