MediaFinder: Collect, enrich and visualize media memes shared by the crowd

Social networks play an increasingly important role for sharing media items related to human's activities, feelings, emotions and conversations opening a window to the world in
real-time. However, these images and videos are spread over multiple social networks. In this paper, we first describe a so-called media server that collect recent images and videos which can be potentially attached to an event. These media items can then be used for the automatic generation of visual summaries. However, making sense out of the resulting media galleries is an extremely challenging task. We present a framework that leverages on: (i) visual features from media items for near-deduplication and (ii) textual features from status updates to enrich, cluster and generate storyboards. A prototype is publicly available at http://mediafinder.eurecom.fr.