Family verification based on similarity of individual family member’s facial segments

Abstract

Humans process faces to recognize family resemblance and act accordingly. Undoubtedly, they are capable of recognizing their kin and family members. In this paper, we study the facts and valid assumptions of facial resemblance in family members' facial segments. Our analysis and psychological studies show that the facial resemblance differs from member to member and depends on image segments. First, we estimate the degree of resemblance of each member's image segment. Then, we propose a novel method to fuse similarity of each member's facial image segments to perform family verification. Employing the proposed approach on the collected 5,400-sample family database achieves considerable improvement compared to the state-of-the-art fusion rule in three designated test scenarios. Experimental results also show that the proposed approach could estimate the similarity slightly more accurate than human perception. We believe the public availableness of the database may advance the development in this domain.