Abstract:
A digital document is represented as a set of codes comprising indices into a feature space comprising a number of subspaces, each code corresponds to one subspace and identifying a cell within the subspace. Each digital document can be represented by a code set, and the code set can be used as selection criteria for identifying a number of digital documents using each digital document's corresponding code set. By way of some non-limiting examples, digital document code sets can be used to identify similar or different digital images, used to identify duplicate or nearly-duplicate digital images, used to identify similar and/or different digital images for inclusion in a recommendation, used to identify and rank digital images in a set of search results.
Abstract:
Disclosed is a system and method for automatically detecting social relationships from consumer image collections. The disclosed systems and methods provide the ability to infer relationships between people thereby creating dynamic social networks from the occurrences of people appearing in digital images. Occurrences of people in pictures can be detected based on known or to be known facial recognition technology. These inferences enable relationship determinations regarding whether the people are family members, friends, acquaintances or merely strangers who happen to be in the same place at the same time. The disclosed detection of such relationships enables the building of intelligent image management systems. Furthermore, based on the detected social relationships, advertisements can be served not solely to a single person, but to multiple people within the scope of the social relationship
Abstract:
Disclosure includes system, method and architecture for selecting supplemental digital content using visual appearance. Digital content that is visually similar, or dissimilar, to digital content requested by a user can he identified and provided for presentation with the requested content. The additional digital content is visually congruent, or visually incongruent, with content requested by a user, such that the additional content is similar, or dissimilar, to the requested content from a visual standpoint. In a presentation of the requested content, the presentation position of each additional content item relative to the presentation position of each requested content can be identified using visual congruence, or visual incongruence.
Abstract:
A digital document is represented as a set of codes comprising indices into a feature space comprising a number of subspaces, each code corresponds to one subspace and identifying a cell within the subspace. Each digital document can be represented by a code set, and the code set can be used as selection criteria for identifying a number of digital documents using each digital document's corresponding code set. By way of some non-limiting examples, digital document code sets can be used to identify similar or different digital images, used to identify duplicate or nearly-duplicate digital images, used to identify similar and/or different digital images for inclusion in a recommendation, used to identify and rank digital images in a set of search results.