US 12,437,577 B2
Techniques for identifying skin color in images having uncontrolled lighting conditions
Christine Elfakhri, Brooklyn, NY (US); Florent Valceschini, Jersey City, NJ (US); Loic Tran, Vincennes (FR); Matthieu Perrot, Orsay (FR); Robin Kips, Paris (FR); and Emmanuel Malherbe, Paris (FR)
Assigned to L'Oreal, Paris (FR)
Filed by L'Oreal, Paris (FR)
Filed on Nov. 30, 2021, as Appl. No. 17/538,449.
Application 17/538,449 is a continuation of application No. 16/516,080, filed on Jul. 18, 2019, granted, now 11,191,342.
Prior Publication US 2022/0079325 A1, Mar. 17, 2022
Int. Cl. G06V 40/16 (2022.01); A45D 44/00 (2006.01); A61B 5/00 (2006.01); B44D 3/00 (2006.01); G01J 3/46 (2006.01); G06N 20/00 (2019.01); G06V 10/56 (2022.01)
CPC G06V 40/161 (2022.01) [A45D 44/005 (2013.01); A61B 5/441 (2013.01); B44D 3/003 (2013.01); G01J 3/46 (2013.01); G06N 20/00 (2019.01); G06V 10/56 (2022.01); A45D 2044/007 (2013.01); A61B 5/0077 (2013.01)] 19 Claims
OG exemplary drawing
 
1. A method of training machine learning models to determine skin colors of faces under different illuminants, the method comprising:
receiving at least one training image that includes a face of a training subject;
receiving tagging information for the at least one training image;
adding the at least one training image and the tagging information to a training data store; and
training at least one machine learning model to determine skin colors of faces using the training data set;
wherein training the at least one machine learning model to determine skin colors of faces using the training data set includes:
training a first machine learning model that processes a training image as input to produce an indication of an illuminant color as an output; and
training a second machine learning model that processes the training image and the indication of the illuminant color as input to produce an indication of skin color as an output.