Explainable kinship: The importance of facial features in kinship recognition

Kinship Recognition, the ability to distinguish between close genetic kin and non-kin, could be of great help in society and safety matters. Previous studies on human kinship recognition found an interesting insight when looking for the most important features. Results showed that analyzing only the top half of a face gives equal or even better performance compared to analyzing the whole face. In this paper, we aim to find the important features for automated kinship recognition based on the theory of human kinship recognition; this set of features was researched using features from pre-trained metrics from the StyleGAN2 model. We found that the most important facial features from the selection of 40 features are mostly focused on the facial hair traits. Furthermore, age-related features were found to be very important. This set of features does not entirely comply with the set of features important in human kinship recognition. Previous research has shown human kinship recognition performance does not decrease when removing the bottom half of the image of the face. In contrast, our results show that for automated kinship recognition, removing either the bottom or the top half of a face results in a decrease in the performance of our classifiers.