Ordinal Measures for Image Correspondence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the 18th international conference on World wide web
Near-duplicate detection for images and videos
LS-MMRM '09 Proceedings of the First ACM workshop on Large-scale multimedia retrieval and mining
Experience Design: Technology for All the Right Reasons
Experience Design: Technology for All the Right Reasons
STORIFY: a tool to assist design teams in envisioning and discussing user experience
CHI '11 Extended Abstracts on Human Factors in Computing Systems
Finding media illustrating events
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Photo stream alignment for collaborative photo collection and sharing in social media
WSM '11 Proceedings of the 3rd ACM SIGMM international workshop on Social media
NERD: a framework for unifying named entity recognition and disambiguation extraction tools
EACL '12 Proceedings of the Demonstrations at the 13th Conference of the European Chapter of the Association for Computational Linguistics
A meteoroid on steroids: ranking media items stemming from multiple social networks
Proceedings of the 22nd international conference on World Wide Web companion
Live topic generation from event streams
Proceedings of the 22nd international conference on World Wide Web companion
MediaFinder: collect, enrich and visualize media memes shared by the crowd
Proceedings of the 22nd international conference on World Wide Web companion
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Social networks play an increasingly important role for sharing media items related to daily life moments or for the live coverage of events. One of the problems is that media are spread over multiple social networks. In this paper, we propose a social network-agnostic approach for collecting recent images and videos which can be potentially attached to an event. These media items can be used for the automatic generation of visual summaries in the form of media galleries. Our approach includes the alignment of the varying search result formats of different social networks, while putting media items in correspondence with the status updates and stories they are related to. More precisely we leverage on: (i) visual features from media items, (ii) textual features from status updates, and (iii) social features from social networks to interpret, deduplicate, cluster, and visualize media items. We address the technical details of media item extraction and media item processing, discuss criteria for media item filtering and envision several visualization options for media presentation. Our evaluation is divided into two parts: first we assess the performances of the image process deduplication and then we propose a human evaluation of the summary creation compared with Teleportd and Twitter media galleries. A demo of our approach is publicly available at http://eventmedia.eurecom.fr/media-finder.