Feature Extraction and a Database Strategy for Video Fingerprinting
VISUAL '02 Proceedings of the 5th International Conference on Recent Advances in Visual Information Systems
Story Segmentation and Detection of Commercials in Broadcast News Video
ADL '98 Proceedings of the Advances in Digital Libraries Conference
On the detection and recognition of television commercials
ICMCS '97 Proceedings of the 1997 International Conference on Multimedia Computing and Systems
Data integration in a bandwidth-rich world
Communications of the ACM - Blueprint for the future of high-performance networking
Predicting Program Guides for Video Structuring
ICTAI '05 Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence
Finding and identifying unknown commercials using repeated video sequence detection
Computer Vision and Image Understanding
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Fast structuring of large television streams using program guides
AMR'06 Proceedings of the 4th international conference on Adaptive multimedia retrieval: user, context, and feedback
ARGOS: automatically extracting repeating objects from multimedia streams
IEEE Transactions on Multimedia
Online Macro-segmentation of Television Streams
MMM '09 Proceedings of the 15th International Multimedia Modeling Conference on Advances in Multimedia Modeling
ASMTA'10 Proceedings of the 17th international conference on Analytical and stochastic modeling techniques and applications
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In this paper, we study different approaches for TV broadcast macro-segmentation. This is needed in many novel services such as TV-on-Demand. TV broadcast macro-segmentation can be performed using either the metadata associated with the stream or by directly analyzing the audiovisual stream. This paper presents both approaches and analyzes their advantages and limitations with respect to applications. It then presents an experimental study. This study has been conducted on real data of more than 5 months of broadcasting. Two types of metadata have been considered and a video identification technique has been developed. The obtained results show in particular, the effectiveness of content-based solution and also highlight imprecision and limitations of metadata. They show in particular that over a 24 hour broadcast, more than 40% of the programs start more than 5 minutes earlier or later than that expected in the metadata.