公开(公告)号：US11553872B2

公开(公告)日：2023-01-17

申请号：US16702895

申请日：2019-12-04

Applicant: L'OREAL

Inventor： Ruowei Jiang ,  Junwei Ma ,  He Ma ,  Eric Elmoznino ,  Irina Kezele ,  Alex Levinshtein ,  Julien Despois ,  Matthieu Perrot ,  Frederic Antoinin Raymond Serge Flament ,  Parham Aarabi

IPC: G06V40/16 ,  A61B5/00 ,  G06T7/00 ,  G06N3/04 ,  G06N3/08 ,  G06V10/82 ,  G06V40/18

Abstract: There is shown and described a deep learning based system and method for skin diagnostics as well as testing metrics that show that such a deep learning based system outperforms human experts on the task of apparent skin diagnostics. Also shown and described is a system and method of monitoring a skin treatment regime using a deep learning based system and method for skin diagnostics.

公开(公告)号：US20250040873A1

公开(公告)日：2025-02-06

申请号：US18708979

申请日：2022-10-21

Applicant: L'Oreal

Inventor： Benjamin Askenazi ,  Matthieu Perrot ,  Emmanuel Malherbe ,  Yohana Pachas ,  Olivier Leseur

IPC: A61B5/00 ,  G06T7/00 ,  G06T7/11 ,  G16H20/00

Abstract: The present invention relates to a method for characterizing eyelashes or eyebrows which is implemented by computer and comprises the following steps, which are directed toward:—receiving data corresponding to a set of pixels in a close-up image of a body area comprising a plurality of eyelashes, preferably the entirety of a row of eyelashes or of an eyebrow, to be characterized:—applying at least one step of computer vision so as to obtain, on the basis of the image data received, a numerical evaluation of at least one characteristic numerical parameter from among, notably, the number of fibers, an average length of the fibers, an average thickness of the fibers, and a curvature of the fibers.

公开(公告)号：US11521013B2

公开(公告)日：2022-12-06

申请号：US17317742

申请日：2021-05-11

Applicant: L'Oreal

Inventor： Grégoire Charraud ,  Helga Malaprade ,  Géraldine Thiebaut ,  Matthieu Perrot ,  Robin Kips

IPC: G06K9/62 ,  G06V10/40 ,  G06V40/16 ,  G06V30/10

Abstract: Embodiments of the present disclosure provide systems, methods, and computer-readable media that use machine learning models to enable computing devices to detect and identify cosmetic products in face images. In some embodiments, a model training system may gather training data for building the machine learning models by analyzing face images associated with tagging data. In some embodiments, a recommendation system may be configured to use the machine learning models generated by the model training system to detect products in face images, and to add information based on the detected products to a look data store, and/or to provide recommendations for similar looks from the look data store based on the detected products.

公开(公告)号：US20220079325A1

公开(公告)日：2022-03-17

申请号：US17538449

申请日：2021-11-30

Applicant: L'Oreal

Inventor： Christine Elfakhri ,  Florent Valceschini ,  Loic Tran ,  Matthieu Perrot ,  Robin Kips ,  Emmanuel Malherbe

IPC: A45D44/00 ,  G06N20/00 ,  A61B5/00 ,  B44D3/00 ,  G01J3/46

Abstract: In some embodiments of the present disclosure, one or more machine learning models are trained to accurately estimate skin color in one or more images regardless of the lighting conditions. In some embodiments, the models can then be used to estimate a skin color in a new image, and that estimated skin color can be used for a variety of purposes. For example, the skin color may be used to generate a recommendation for a foundation shade that accurately matches the skin color, or a recommendation for another cosmetic product that is complimentary with the estimated skin color. Thus, the need for an in-person test of the product is eliminated.

公开(公告)号：US20210264204A1

公开(公告)日：2021-08-26

申请号：US17317742

申请日：2021-05-11

Applicant: L'Oreal

Inventor： Grégoire Charraud ,  Helga Malaprade ,  Géraldine Thiebaut ,  Matthieu Perrot ,  Robin Kips

IPC: G06K9/62 ,  G06K9/00 ,  G06K9/46

Abstract: Embodiments of the present disclosure provide systems, methods, and computer-readable media that use machine learning models to enable computing devices to detect and identify cosmetic products in face images. In some embodiments, a model training system may gather training data for building the machine learning models by analyzing face images associated with tagging data. In some embodiments, a recommendation system may be configured to use the machine learning models generated by the model training system to detect products in face images, and to add information based on the detected products to a look data store, and/or to provide recommendations for similar looks from the look data store based on the detected products.

公开(公告)号：US12159397B2

公开(公告)日：2024-12-03

申请号：US17277166

申请日：2019-07-15

Applicant: L'OREAL

Inventor： Matthieu Perrot ,  Emmanuel Malherbe ,  Thierry Wasserman ,  John Charbit ,  Panagiotis-alexandros Bokaris

IPC: G06T7/00 ,  A61B5/00 ,  G06T7/10 ,  G06T7/90

Abstract: The present application is directed to a method and system for determining at least one physical and/or chemical characteristic of a keratinous surface of a user, the method comprising the steps of: —receiving data corresponding to at least one image of the keratinous surface, —processing the image by applying at least one machine learning model to said image, —returning at least one numerical value corresponding to a grade of the characteristic of the keratinous surface to be determined.

公开(公告)号：US20210015240A1

公开(公告)日：2021-01-21

申请号：US16516080

申请日：2019-07-18

Applicant: L'Oreal

Inventor： Christine Elfakhri ,  Florent Valceschini ,  Loic Tran ,  Matthieu Perrot ,  Robin Kips ,  Emmanuel Malherbe

IPC: A45D44/00 ,  A61B5/00 ,  G06N20/00 ,  B44D3/00 ,  G01J3/46

Abstract: In some embodiments of the present disclosure, one or more machine learning models are trained to accurately estimate skin color in one or more images regardless of the lighting conditions. In some embodiments, the models can then be used to estimate a skin color in a new image, and that estimated skin color can be used for a variety of purposes. For example, the skin color may be used to generate a recommendation for a foundation shade that accurately matches the skin color, or a recommendation for another cosmetic product that is complimentary with the estimated skin color. Thus, the need for an in-person test of the product is eliminated.

公开(公告)号：US12067645B2

公开(公告)日：2024-08-20

申请号：US17363098

申请日：2021-06-30

Applicant: L'Oreal

Inventor： Julien Despois ,  Frederic Flament ,  Matthieu Perrot

IPC: G06T11/00 ,  A45D44/00 ,  G06N3/045 ,  G06N3/088 ,  G06Q30/0601 ,  G06T7/00 ,  G06V10/44 ,  G06V10/50 ,  G06V10/764 ,  G06V10/774 ,  G06V10/82 ,  G06V40/16

CPC classification number: G06T11/00 ,  A45D44/005 ,  G06N3/045 ,  G06N3/088 ,  G06Q30/0631 ,  G06Q30/0643 ,  G06T7/0012 ,  G06V10/454 ,  G06V10/50 ,  G06V10/764 ,  G06V10/765 ,  G06V10/774 ,  G06V10/82 ,  G06V40/171 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30088 ,  G06T2207/30201

Abstract: There are provided computing devices and methods, etc. to controllably transform an image of a face, including a high resolution image, to simulate continuous aging. Ethnicity-specific aging information and weak spatial supervision are used to guide the aging process defined through training a model comprising a GANs based generator. Aging maps present the ethnicity-specific aging information as skin sign scores or apparent age values. The scores are located in the map in association with a respective location of the skin sign zone of the face associated with the skin sign. Patch-based training, particularly in association with location information to differentiate similar patches from different parts of the face, is used to train on high resolution images while minimize resource usage.

公开(公告)号：US11832958B2

公开(公告)日：2023-12-05

申请号：US18080331

申请日：2022-12-13

Applicant: L'OREAL

Inventor： Ruowei Jiang ,  Junwei Ma ,  He Ma ,  Eric Elmoznino ,  Irina Kezele ,  Alex Levinshtein ,  Julien Despois ,  Matthieu Perrot ,  Frederic Antoinin Raymond Serge Flament ,  Parham Aarabi

IPC: A61B5/00 ,  G06T7/00 ,  G06V40/16 ,  G06N3/08 ,  G06V10/82 ,  G06N3/045 ,  G06V10/44 ,  G06V40/18

CPC classification number: A61B5/441 ,  G06N3/045 ,  G06N3/08 ,  G06T7/0012 ,  G06V10/454 ,  G06V10/82 ,  G06V40/171 ,  G06T2207/30088 ,  G06V40/174 ,  G06V40/18

Abstract: There is shown and described a deep learning based system and method for skin diagnostics as well as testing metrics that show that such a deep learning based system outperforms human experts on the task of apparent skin diagnostics. Also shown and described is a system and method of monitoring a skin treatment regime using a deep learning based system and method for skin diagnostics.

公开(公告)号：US11191342B2

公开(公告)日：2021-12-07

申请号：US16516080

申请日：2019-07-18

Applicant: L'Oreal

Inventor： Christine Elfakhri ,  Florent Valceschini ,  Loic Tran ,  Matthieu Perrot ,  Robin Kips ,  Emmanuel Malherbe

IPC: A45D44/00 ,  G06N20/00 ,  A61B5/00 ,  B44D3/00 ,  G01J3/46

Abstract: In some embodiments of the present disclosure, one or more machine learning models are trained to accurately estimate skin color in one or more images regardless of the lighting conditions. In some embodiments, the models can then be used to estimate a skin color in a new image, and that estimated skin color can be used for a variety of purposes. For example, the skin color may be used to generate a recommendation for a foundation shade that accurately matches the skin color, or a recommendation for another cosmetic product that is complimentary with the estimated skin color. Thus, the need for an in-person test of the product is eliminated.