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Distance Estimation of an Unknown Person from a Portrait
Xavier P. Burgos-Artizzu1, 2, Matteo Ruggero Ronchi2, and Pietro Perona2
1Technicolor - Cesson Sévigné, France
xavier.burgos@technicolor.com
2California Institute of Technology, Pasadena, CA, USA
mronchi@caltech.edu
perona@caltech.edu
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.
Keywords: Camera-subject distance, Perspective distortion, Pose estimation, Face recognition
LNCS 8689, p. 313 ff.
lncs@springer.com
© Springer International Publishing Switzerland 2014