Tri-subjects kinship verification: Understanding the core of a family

Recent research has demonstrated that computer vision algorithms have understood individual face image fairly well. However, one major challenge in computer vision is to go beyond that and to investigate the bi-or tri- relationship among multiple visual entities, answering such questions as whether a child in a photo belongs to given parents. Indeed parents-child relationship plays a core role in a family and understanding such kind of kin relationship would have fundamental impact on the behavior of an artificial intelligent agent working in a human being world. In this work, we tackle the problem of tri-subjects kinship verification by effectively exploiting the dependence structure between child and parents in a few aspects: similarity measure, feature selection and classifier design. State-of-the-art results are reported with the proposed method on our newly released kinship database characterized by over 1,000 parents-child groups.