Story Segmentation and Detection of Commercials in Broadcast News Video
ADL '98 Proceedings of the Advances in Digital Libraries Conference
Detecting image near-duplicate by stochastic attributed relational graph matching with learning
Proceedings of the 12th annual ACM international conference on Multimedia
Tracking news stories across different sources
Proceedings of the 13th annual ACM international conference on Multimedia
Proceedings of the 6th ACM international conference on Image and video retrieval
Novelty detection for cross-lingual news stories with visual duplicates and speech transcripts
Proceedings of the 15th international conference on Multimedia
Scene duplicate detection based on the pattern of discontinuities in feature point trajectories
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Scalable mining of large video databases using copy detection
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Scalable detection of partial near-duplicate videos by visual-temporal consistency
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Mining TV broadcasts for recurring video sequences
Proceedings of the ACM International Conference on Image and Video Retrieval
An efficient near-duplicate video shot detection method using shot-based interest points
IEEE Transactions on Multimedia
IEEE Transactions on Audio, Speech, and Language Processing
AIEMPro '11 Proceedings of the 2011 ACM international workshop on Automated media analysis and production for novel TV services
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TV news programs are important target of multimedia content analysis since they are one of major information sources for ordinary daily lives. Since the computer storage cost has reduced significantly, today we can digitally archive a huge amount of TV news programs. On the other hand, as the archive size grows larger, the cost for browsing and utilizing video archives also increases significantly. To circumvent this problem, we present a visualization method of TV news shots using the popularity-based filtering across multiple TV channels. This method can be regarded as social filtering by TV broadcasters or popularity ranking among TV channels. In order to examine the effectiveness of our approach, we conducted an experiment against a thousand-hour order video archive storing 6 TV-channel streams for one month long. To our best knowledge, there is no former work applying this scheme to such a huge archive with conducting quantitative evaluation.