Display screen with animated graphical user interface

A computer-implemented method for targeting marketing content to an online user, includes the steps of collecting data describing the user in a user profile, comparing the user profile with a target profile and presenting the user with content based on the comparison. The user profile includes a photographic likeness of the user, as well as information derived from the user's photographic likeness. Certain content may be dynamically created for the user based on the user profile and may include the photographic likeness of the user, which may be altered to incorporate a portion of the content into the photographic likeness. In this manner, personalized advertisements for cosmetics, jewelry, clothing and other items may be created. The user profile also includes data describing the user's browsing habits and responses to context-specific survey questions. In one embodiment, metrics are assigned to the user profile data, and a data index identifying the user's preferences and purchasing habits is calculated for the user based on the assigned metrics. Each metric may also have an associated confidence factor, which causes the metric value to decay over time.

Targeted marketing system and method

In one embodiment, a method includes receiving multiple images from multiple cameras, where the multiple cameras include a first camera having a first orientation and a second camera having a second orientation, and the multiple images include a first image from the first camera and a second image from the second camera. The method also includes detecting multiple feature points within the first and second images. The method further includes determining one or more pairs of corresponding feature points located within a region of overlap between the first and second images, where the pairs of corresponding feature points include a respective one of the feature points from each of the first and second images. The method also includes spatially adjusting the first or second image based on a calculated offset between each pair of corresponding feature points.

Image stitching for three-dimensional video

Systems and methods of quickly recognizing or differentiating many objects are presented. Contemplated systems include an object model database storing recognition models associated with known modeled objects. The object identifiers can be indexed in the object model database based on recognition features derived from key frames of the modeled object. Such objects are recognized by a recognition engine at a later time. The recognition engine can construct a recognition strategy based on a current context where the recognition strategy includes rules for executing one or more recognition algorithms on a digital representation of a scene. The recognition engine can recognize an object from the object model database, and then attempt to identify key frame bundles that are contextually relevant, which can then be used to track the object or to query a content database for content information.

Fast recognition algorithm processing, systems and methods

A mobile app for a mobile device includes logic for an overlay for the UI of the mobile device, and a location on the UI where the overlay is to be displayed, as specified by the user. The mobile app also comprises a scanning layer to create a list of items to be located and acquired. Instructions for locating the items, and objectives for ordering the locations of the items on the overlay are received from the user. The objectives may be for a trip to acquire the items, such as total cost, time, number of stops, preferred establishments for acquiring the items, preferred brands of the items, and other bases. The locations of the items are identified and filtered in accordance with the instructions. The locations of the items are displayed on the overlay at the area of the user interface specified by the user, according to geographical location.

Shopping list creator and optimizer

Methods for generating and sharing a virtual body model of a person, created with a small number of measurements and a single photograph, combined with one or more images of garments. The virtual body model represents a realistic representation of the users body and is used for visualizing photo-realistic fit visualizations of garments, hairstyles, make-up, and/or other accessories. The virtual garments are created from layers based on photographs of real garment from multiple angles. Furthermore the virtual body model is used in multiple embodiments of manual and automatic garment, make-up, and, hairstyle recommendations, such as, from channels, friends, and fashion entities. The virtual body model is sharable for, as example, visualization and comments on looks. Furthermore it is also used for enabling users to buy garments that fit other users, suitable for gifts or similar. The implementation can also be used in peer-to-peer online sales where garments can be bought with the knowledge that the seller has a similar body shape and size as the user.

Computer implemented methods and systems for generating virtual body models for garment fit visualisation

A computer-implemented garment size recommendation and fit analysis system in which a memory stores a virtual profile or model of an end-user and a processor is programmed to receive an end-user's selection of a garment and to then determine, using a garment fit algorithm, how well that garment will fit the end-user's profile or model, and in which the algorithm is trained on actual sales data.

Garment size recommendation and fit analysis system and method

A virtual body model of a person is created with a small number of measurements and a single photograph and combined with one or more images of garments. The virtual body model represents a realistic representation of the userâ s body and is used for visualizing photo-realistic fit visualizations of garments, hairstyles, make-up, and / or other accessories. The virtual garments are created from layers based on photographs of real garment from multiple angles. Furthermore the virtual body model is used in multiple embodiments of manual and automatic garment, make-up, and, hairstyle recommendations, such as, from channels, friends, and fashion entities. The virtual body model is sharable for, as example, visualization and comments on looks. Furthermore it is also used for enabling users to buy garments that fit other users, suitable for gifts or similar. The implementation can also be used in peer-to-peer online sales where garments can be bought with the knowledge that the seller has a similar body shape and size as the user as well as being used in manufacturing the garment chosen.

Using a body model of a user to show fit of clothing

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Computer implemented methods and systems for generating virtual body models for garment fit visualisation

Garment size recommendation and fit analysis system and method

Using a body model of a user to show fit of clothing