There are broadly two approaches to creating hard classification problems suitable for research. The first is to impoverish the stimuli, thereby making them harder to categorize. This can be done by obscuring various portions of a face (Gosselin & Schyns,
2001; Scheirer, Anthony, Nakayama, & Cox,
2014), adding noise (Gold, Bennett, & Sekuler,
1999), binarizing (Kozunov, Nikolaeva, & Stroganova,
2018), or blurring faces (Steinmetz & DaSilva,
2006). Alternatively, the categories themselves can be made more fine-grained, thereby increasing task difficulty. While there has been some work on discriminating between finer grained geographical origin, such as with Chinese/Japanese/Korean (Y. Wang et al.,
2016), Chinese subethnicities (Duan et al.,
2010), and Myanmar (Tin & Sein,
2011), these studies have not systematically characterized human performance. In fact, it is an open question whether and how well humans can discriminate fine-grained face attributes across various world populations.