Radiometric Calibration From Faces in Images

Chen Li, Stephen Lin, Kun Zhou, Katsushi Ikeuchi; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, pp. 3117-3126


We present a method for radiometric calibration of cameras from a single image that contains a human face. This technique takes advantage of a low-rank property that exists among certain skin albedo gradients because of the pigments within the skin. This property becomes distorted in images that are captured with a non-linear camera response function, and we perform radiometric calibration by solving for the inverse response function that best restores this low-rank property in an image. Although this work makes use of the color properties of skin pigments, we show that this calibration is unaffected by the color of scene illumination or the sensitivities of the camera's color filters. Our experiments validate this approach on a variety of images containing human faces, and show that faces can provide an important source of calibration data in images where existing radiometric calibration techniques perform poorly.

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author = {Li, Chen and Lin, Stephen and Zhou, Kun and Ikeuchi, Katsushi},
title = {Radiometric Calibration From Faces in Images},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {July},
year = {2017}