Quantitative analysis of human facial beauty using geometric features

Perception of human facial beauty is an important aspect of human intelligence and has attracted interests of researchers from diverse fields such as psychology and computer science. Previous studies, however, have the following limitations. First, they did not well quantify the facial feature space. Second, they seldom consider the transformation occurring to faces or the physical sizes of faces. Third, most of them require intensive manual work, e.g. marking landmarks. To overcome these limitations, this paper maps faces onto a human face shape space, and then quantitatively analyses the effect of facial geometric features on human facial beauty by using a similarity transformation invariant shape distance measurement and advanced automatic image processing techniques. With the proposed methodology, we experiment on tens of thousands of female and male faces, revealing that human face shapes lie in a very compact region of the geometric feature space and that female and male average face shapes are very similar. Further, we demonstrate that a face can become more beautiful by making its geometric feature getting obviously closer to the average face shape, but if its distance to the average face shape is already relatively small, deforming it further toward the average face shape cannot effectively improve its attractiveness.