Contribution of shape and surface reflectance information to kinship detection in 3D face images

Citation

Lee A, Fasolt V, Holzleitner I, O'Shea K & DeBruine L (2019) Contribution of shape and surface reflectance information to kinship detection in 3D face images. Journal of Vision, 19 (12) p. 9, Art. No.: 9. https://doi.org/10.1167/19.12.9

Abstract
Previous research has established that humans are able to detect kinship among strangers from facial images alone. The current study investigated what facial information is used for making those kinship judgments, specifically the contribution of face shape and surface reflectance information (e.g., skin texture, tone, eye and eyebrow colour). Using 3D facial images, 195 participants were asked to judge the relatedness of one hundred child pairs, half of which were related and half of which were unrelated. Participants were randomly assigned to judge one of three stimulus versions: face images with both surface reflectance and shape information present (reflectance and shape version), face images with shape information removed but surface reflectance present (reflectance version) or face images with surface reflectance information removed but shape present (shape version). Using binomial logistic mixed models, we found that participants were able to detect relatedness at levels above chance for all three stimulus versions. Overall, both individual shape and surface reflectance information contribute to kinship detection, and both cues are optimally combined when presented together. Preprint, pre-registration, code and data are available on the Open Science Framework (osf.io/7ftxd).

Keywords
kinship; face perception; allocentric kin recognition; facial resemblance; 3D face shape; surface reflectance information

Journal
Journal of Vision: Volume 19, Issue 12

People

Dr Anthony Lee

Lecturer in Psychology, Psychology