Can faces verify blood-relations?

Humans can verify unknown parent-offspring and sibling pairs over unrelated subject pairs. A computational scheme to accomplish the task robustly, in the presence of challenges due to gender and age gap between related-pairs, finds many applications such as matching orphaned/lost children, identifying relatives from a photo collection. We propose one of the first computational schemes to verify sibling pairs along with parent-child relation. Towards the same, we present a novel ensemble metric learning scheme that combines the advantages of task-specific learning, adaptive prototype and feature selection and ‘late fusion’. We demonstrate the robustness of the scheme on a very large scale, real-world dataset. Specifically, we show that the gender difference among related-pairs leads to lower performance of traditional verification and metric learning algorithms. Through various experiments, we quantitatively study the robustness of the proposed scheme in the general and speci...

• Type: Conference
• Year: 2012
• Where: BTAS
• Authors: Gowri Somanath, Chandra Kambhamettu
• Keywords: Blood-relations, Ensemble Metric Learning, Facial Image Analysis, Kinship