Image Metrics Limited

Tomos G Williams

Kevin Walker

Michael Rogers

Martin Tosas

Salil Deena

Martin De La Gorce

Martin DeLa Gorce

Computer-implemented methods for vending at least one cosmetic product to a first consumer. A real-time image of a portion of a body of the consumer is captured using a personal computational device and the consumer provides a desired makeup look via the personal computational device. The desired makeup look is then applied to an image of the portion of the body of the consumer, thereby generating a composite image of the portion of the body of the first consumer with the desired makeup look, and a retail order for the cosmetic product is received from the consumer. The order may be received before or after the consumer's image is captured. Another consumer, or a product specialist, may be involved in the aforesaid process via a computer communications link.

Monetization using video-based simulation of cosmetic products

Computer-implemented methods for real-time simulation of the application of one or more cosmetic products to a portion of the body of a user being imaged in an image-capture environment that is subject to uncertain lighting conditions. A real-time image of a portion of the user is captured and used to derive both image-capture environment parameters and user visual characteristics. Based on a desired look received from the user, a correspondence is extracted between the desired look and the pertinent portion of the user so that the desired look can be adapted to the image-capture environment parameters and the user's visual characteristics, and the adapted look is applied to an image of the user.

Adaptive, calibrated simulation of cosmetic products on consumer devices

Computerized methods for creating tracks of locations across frames of a video corresponding to a facial feature of a human. A set of feature location hypotheses is generated, as applied to images derived from the sequence of frames representing images of the human. Each hypothesis is refined, and a first set of confidence measures is associated with each hypothesis. A second set of confidence measures is associated with interframe transition, and a cost function that is a combination of hypotheses and transition confidence measures is minimized. A set of tracks is generated, characterizing each of a plurality of facial features within each frame of the sequence of frames. Performance analysis data may further be derived in a performance driven animation production pipeline, based on the generated tracks.

Optimal automatic capture of facial movements and expressions in video sequences

Computer implemented methods for generating a non-transient record of feature locations and/or facial expression parameters characterizing a person's face. A video sequence of a specified individual person is received and a feature locator update model is applied to the video sequence. The feature locator update model is derived by defining a set of training images, generating a set of facial feature displacements for each training image with associated image sample vectors, and training a regularized linear regression which maps from image sample vectors to displacement vectors, wherein the regularization includes a spatial smoothness term within the shape-free sample space. A feature location and/or a facial expression parameter is then extracted, based on the feature update model, characterizing the location, and/or the expression, of the feature of the face of the specified individual person.

Building systems for tracking facial features across individuals and groups

Computer implemented methods for generating a non-transient record of feature locations and/or facial expression parameters characterizing a person's face. A video sequence of a specified individual person is received and a feature locator update model is applied to the video sequence. The feature locator update model is derived by defining a set of training images, generating a set of facial feature displacements for each training image with associated image sample vectors, and training a regularized linear regression which maps from image sample vectors to displacement vectors, wherein the regularization includes a spatial smoothness term within the shape-free sample space. A feature location and/or a facial expression parameter is then extracted, based on the feature update model, characterizing the location, and/or the expression, of a selected set of features of the face of the specified individual person that correspond to an adaptive set of feature locations.

Growing community of inventors

Rhuthun, United Kingdom

Tomos G Williams