Context-aware image semantic extraction in the social web.

Media sharing applications such as Panoramio and Flickr contain a huge amount of pictures that need to be organized to facilitate browsing and retrieval. Such pictures are often surrounded by a set of metadata or image tags, constituting the image context. With the advent of the paradigm of Web 2.0 especially the past five years, the concept of image context has further evolved, allowing users to tag their own and other people's pictures. Focusing on tagging, we distinguish between static and dynamic features. The set of static features include textual and visual features, as well as the contextual information. Further, we may identify other features belonging to the social context as a result of the usage within the media sharing applications. Due to their dynamic nature, we call these the dynamic set of features. In this work, we assume that every media uploaded contains both static and dynamic features. In addition, a user may be linked with other users with whom he/she shares common interests. This has resulted in a new series of challenges within the research field of semantic understanding. One of the main goals of this work is to address these challenges.