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Facial kinship verification aims at automatically determining whether twosubjects have a kinship relation. It has been widely studied from differentmodalities, such as faces, voices, gait, and smiling expressions. However, thepotential of bio-signals, such as remote Photoplethysmography (rPPG) extractedfrom facial videos, remains largely unexplored in the kinship verificationproblem. In this paper, we investigate for the first time the usage of the rPPGsignal for kinship verification. Specifically, we proposed a one-dimensionalConvolutional Neural Network (1DCNN) with a 1DCNN-Attention module andcontrastive loss to learn the kinship similarity from rPPGs. The network takesmultiple rPPG signals extracted from various facial Regions of Interest (ROIs)as inputs. Additionally, the 1DCNN attention module is designed to learn andcapture the discriminative kin features from feature embeddings. Finally, theproposed method is evaluated on the UvANEMO Smile Database from different kinrelations, showing the usefulness of rPPG signals in verifying kinship.

Kinship Verification from rPPG using 1DCNN Attention networks