Abstract: In an embodiment, a virtual hair coloration system includes: a projector 22 configured to project digital content including a makeup application tutorial onto the user's hair; and a dynamic mapping unit 24; 30 operably coupled to the projector, wherein the dynamic mapping unit is configured to establish a dynamic correspondence between pixels of the projector 22 and features of the user's hair.

Abstract: The present invention relates to a method for determining, from a set of physical elements (10), a specific value of an input data for a tool (12) for determining a customized cosmetic action for an individual (I), each physical element (10) having a sensory property representative of a characteristic of a body zone and associated with an identifier, each identifier being associated with a predefined value of said input data characterizing said body zone according to a match table, the method comprising the following steps:—selecting a physical element (10) for the individual (I) among the set of physical elements (10), —acquiring, via the calculator (14), the identifier of the selected physical element (10), and—determining, via the calculator (14), the predefined value of the input data corresponding to the identifier acquired according to the match table.

Abstract: In an embodiment, a makeup application system includes: a projector (22) configured to project digital content including a makeup application tutorial onto the user's facial surface; and a dynamic mapping unit (24); (30) operably coupled to the projector, wherein the dynamic mapping unit is configured to establish a dynamic correspondence between pixels of the projector (22) and features of the user's facial surface.

Abstract: In an embodiment, a virtual hair coloration system includes: a projector 22 configured to project digital content including a makeup application tutorial onto the user's hair; and a dynamic mapping unit 24; 30 operably coupled to the projector, wherein the dynamic mapping unit is configured to establish a dynamic correspondence between pixels of the projector 22 and features of the user's hair.

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.

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.

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.

Abstract: Systems and methods for predicting a Sun Protection Factor (SPF) in vitro, such as by spectral/image analysis, of a sunscreen formulation are described.

Abstract: Systems and methods for predicting a Sun Protection Factor (SPF) in vitro, such as by spectral/image analysis, of a sunscreen formulation are described.