A semi-automatic approach to home video editing
UIST '00 Proceedings of the 13th annual ACM symposium on User interface software and technology
OM-based video shot retrieval by one-to-one matching
Multimedia Tools and Applications
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KI '08 Proceedings of the 31st annual German conference on Advances in Artificial Intelligence
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ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
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ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
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In this paper, we describe a unique new paradigm for video database management known as ViBE (video indexing and browsing environment). ViBE is a browseable/searchable paradigm for organizing video data containing a large number of sequences. The system first segments video sequences into shots by using a new feature vector known as the Generalized Trace obtained from the DC-sequence of the compressed data. Each video shot is then represented by a hierarchical structure known as the shot tree. The shots are then classified into pseudo-semantic classes that describe the shot content. Finally, the results are presented to the user in an active browsing environment using a similarity pyramid data structure. The similarity pyramid allows the user to view the video database at various levels of detail. The user can also define semantic classes and reorganize the browsing environment based on relevance feedback. We describe how ViBE performs on a database of MPEG sequences.