Kinship verification based on status-aware projection learning
Haijun Liu, Jian Cheng, Wang Feng · 2017
Kinship verification for parent-child is considered to be an asymmetric metric process, in which parents and children are associated with different status where the parents are priorly known to be significantly older than the children. To address the asymmetric metric learning, a status-aware projection learning (SaPL) method is proposed for facial image-based kinship verification, especially for the parent-child kinship. SaPL learns two status-specific projections to capture the significant appearance commonality between parents and children, respectively. Each status-specific projection consists of two components: a common component shared by the two status projections and a status-specific component. SaPL generally outperforms the one Mahalanobis distance metric. Extensive experimental results and comparisons with state-of-the-art approaches demonstrate the effectiveness of the proposed SaPL for kinship verification.