Isabelle Boutet¹, Ashlyne Rayne¹, Arda Erbayav¹, Alice O'Toole²; ¹University of Ottawa, ²University of Texas at Dallas

Background: Face distinctiveness is a pivotal concept in face recognition, due to long-standing findings indicating that the rated typicality of a face is inversely related to its recognizability (e.g., Light et al., 1979). Many studies on face distinctiveness rely on human evaluations, typically of frontally-viewed faces (Johnston & Edmonds, 2009). In real-life interactions, faces are perceived from images that vary widely, including across different illumination and viewpoint conditions (Burton, 2013). To better reflect this reality, there is growing interest in understanding face perception across image variations. Research on social traits suggests that some evaluations are more consistent across image variations than others (e.g. Gogan et al., 2021; Todorov and Porter, 2014; Sutherland, Youngs, & Rhodes, 2017). We investigated whether distinctiveness evaluations are consistent across different image formats. Methods: Participants (N = 459; aged 17-35) rated a set of eight randomly assigned identities from a sample of 65 male and 64 female identities taken from the FIE database (de Oliveira Junior & Thomaz, 2006). Participants rated each identity across 3 image formats (half of the right profile and two front profiles, one under darker illumination). Faces were rated for distinctiveness (memorable, typical, common) and social traits (e.g., humble, interesting) (Bainbridge et al., 2013; Oosterhof & Todorov, 2008). Results: Distinctiveness ratings were consistent across image formats (r ranging from .63 to .84). For social traits, ratings were most consistent across image formats for attractiveness (all r = .90) followed by humble (all r = .89). Conclusion: Human ratings of distinctiveness are stable across image formats. This suggests that distinctiveness ratings are based on stable cues derived from the face itself, rather than from a combination of the face and specific image conditions. This study lays the foundation for future, more ecologically valid research, on the impact of distinctiveness on face recognition.

Acknowledgements: Funding: Supported by the Natural Sciences and Engineering Research Council of Canada Discovery Grant (2022-03998).