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Radiometric Calibration from Faces in Images

Authors: Chen Li 0031; Stephen Lin 0001; Kun Zhou 0001; Katsushi Ikeuchi;

Radiometric Calibration from Faces in Images

Abstract

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 cameras 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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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Average
Average
Top 10%
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