Abstract: Disclosed is a method for building a neural network tool to determine, by processing a picture of a human face, a score representative of a qualitative feature of the face, including performing a training session of an initial neural network to assess, from the picture, an estimated age of the person. The initial neural network includes layers of neurons and associated weights, and each training session is performed on a first database of face images with associated ages, and each training session outputs an updated version of the neural network with adjusted weights. For each updated version of the initial neural network corresponding to a training session, evaluating an error of part of the initial neural network on another database of images with each associated with a reference score representing the qualitative feature, selecting the part of the initial neural network in the updated version corresponding to the minimum.

Abstract: Disclosed is a method for analyzing facial features of a person, including the steps of: acquiring a picture of the face of the person; delimiting, on the picture, at least two zones of the face of the person; processing the picture to determine contrast values of each of the at least two zones; and based on the determined contrast values, determining a cluster to which the person pertains among a plurality of pre-established clusters, with the pre-established clusters being elaborated based on a set of contrast values determined for the same zones of the faces of a reference population in respective pictures of the faces; and providing the person with personalized information, wherein the personalized information depends on the cluster to which the person pertains.

Abstract: A method for modelling age-related traits of a face, from a picture of the face is provided, wherein the age-related traits are either wrinkles or age spots, the method including: for each age-related trait of the face of the same nature, generating a vector including parameters of shape and appearance of the trait; and generating, from the generated vectors, a single representation vector modeling the age-related traits of the same nature in the face. The single representation vector stores information regarding the number of traits in the face and joint probabilities, over the face, of the shape and appearance features of the traits.

Abstract: Disclosed is a method for building a neural network tool to determine, by processing a picture of a human face, a score representative of a qualitative feature of the face, including performing a training session of an initial neural network to assess, from the picture, an estimated age of the person. The initial neural network includes layers of neurons and associated weights, and each training session is performed on a first database of face images with associated ages, and each training session outputs an updated version of the neural network with adjusted weights. For each updated version of the initial neural network corresponding to a training session, evaluating an error of part of the initial neural network on another database of images with each associated with a reference score representing the qualitative feature, selecting the part of the initial neural network in the updated version corresponding to the minimum.

Abstract: Disclosed is a method for modelling age-related traits of a face, from a picture of the face, wherein the age-related traits are either wrinkles or age spots, the method including: for each age-related trait of the face of the same nature, generating a vector including parameters of shape and appearance of the trait; and generating, from the generated vectors, a single representation vector modeling the age-related traits of the same nature in the face. The single representation vector stores information regarding the number of traits in the face and joint probabilities, over the face, of the shape and appearance features of the traits.

Abstract: Disclosed is a method for analyzing facial features of a person, including the steps of: acquiring a picture of the face of the person; delimiting, on the picture, at least two zones of the face of the person; processing the picture to determine contrast values of each of the at least two zones; and based on the determined contrast values, determining a cluster to which the person pertains among a plurality of pre-established clusters, with the pre-established clusters being elaborated based on a set of contrast values determined for the same zones of the faces of a reference population in respective pictures of the faces; and providing the person with personalized information, wherein the personalized information depends on the cluster to which the person pertains.