semantic structuring and retrieval of event chapters in social photo collections
The phenomenal growth of multimedia content on the web over the last couple of decades has paved the way for content management systems integrating intelligent information retrieval and indexing techniques. Also, in order to improve the performance of retrieval techniques while searching and navigating the database, many relevance feedback algorithms are implemented, in which the subjective semantics of individual users are included in the image search. Following the recent developments in social networking, there is an emerging interest to share experiences online with friends using multimedia data. As the experiences to be shared among social peers vary from a simple social gathering to a tourism visit with a group of peers, there is a critical need for intelligent content management tools driven by a social perspective. Addressing the challenges related to socially-driven content management, the objective of this paper is twofold. First, we investigate techniques to intelligently structure multimedia content to enable efficient browsing of photo albums. The proposed structuring schemes exploit EXIF metadata, visual content and social peer relationships. Second, we propose a retrieval model based on social context to identify users with similar interests. The retrieval model aims to allow increased interaction among social peers. The proposed techniques have been evaluated against tourism pictures captured across Europe.
exif metadata social context metadata fusion user generated content particle swarm optimisation image retrieval