Exploring the geo-dependence of human face appearance

The expected appearance of a human face depends strongly on age, ethnicity and gender. While these relationships are well-studied, our work explores the little-studied dependence of facial appearance on geographic location. To support this effort, we constructed GeoFaces, a large dataset of geotagged face images. We examine the geo-dependence of Eigenfaces and use two supervised methods for extracting geo-informative features. The first, canonical correlation analysis, is used to find location-dependent component images as well as the spatial direction of most significant face appearance change. The second, linear discriminant analysis, is used to find countries with relatively homogeneous, yet distinctive, facial appearance.