Distance Estimation of an Unknown Person from a Portrait

Abstract

We propose the first automated method for estimating distance from frontal pictures of unknown faces. Camera calibration is not necessary, nor is the reconstruction of a 3D representation of the shape of the head. Our method is based on estimating automatically the position of face and head landmarks in the image, and then using a regressor to estimate distance from such measurements. We collected and annotated a dataset of frontal portraits of 53 individuals spanning a number of attributes (sex, age, race, hair), each photographed from seven distances. We find that our proposed method outperforms humans performing the same task. We observe that different physiognomies will bias systematically the estimate of distance, i.e. some people look closer than others. We expire which landmarks are more important for this task.