Syntactic clustering of the Web
Selected papers from the sixth international conference on World Wide Web
Cluster ensembles --- a knowledge reuse framework for combining multiple partitions
The Journal of Machine Learning Research
Clustering near-duplicate images in large collections
Proceedings of the international workshop on Workshop on multimedia information retrieval
Synchronization of multi-camera video recordings based on audio
Proceedings of the 15th international conference on Multimedia
Introduction to Information Retrieval
Introduction to Information Retrieval
Less talk, more rock: automated organization of community-contributed collections of concert videos
Proceedings of the 18th international conference on World wide web
A comparison of extrinsic clustering evaluation metrics based on formal constraints
Information Retrieval
Unstructured video-based rendering: interactive exploration of casually captured videos
ACM SIGGRAPH 2010 papers
Automatic mashup generation from multiple-camera concert recordings
Proceedings of the international conference on Multimedia
Crowdsourcing rock n' roll multimedia retrieval
Proceedings of the international conference on Multimedia
Finding media illustrating events
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Automatic generation of video narratives from shared UGC
Proceedings of the 22nd ACM conference on Hypertext and hypermedia
IEEE Transactions on Pattern Analysis and Machine Intelligence
Identifying content for planned events across social media sites
Proceedings of the fifth ACM international conference on Web search and data mining
Socially-aware multimedia authoring: Past, present, and future
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) - Special Sections on the 20th Anniversary of ACM International Conference on Multimedia, Best Papers of ACM Multimedia 2012
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As the amount of social video content captured at physical-world events, and shared online, is rapidly increasing, there is a growing need for robust methods for organization and presentation of the captured content. In this work, we significantly extend prior work that examined automatic detection of videos from events that were captured at the same time, i.e. "overlapping". We go beyond finding pairwise matches between video clips and describe the construction of scenes, or sets of multiple overlapping videos, each scene presenting a coherent moment in the event. We test multiple strategies for scene construction, using a greedy algorithm to create a mapping of videos into scenes, and a clustering refinement step to increase the precision of each scene. We evaluate the strategies in multiple settings and show that a greedy and clustering approach results in best possible balance between recall and precision for all settings.