Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

7-2006

Abstract

Rushes footage are considered as cheap gold mine with the potential for reuse in broadcasting and filmmaking industries. However, it is difficult to mine the "gold" from the rushes since usually only minimum metadata is available. This paper focuses on the structuring and indexing of the rushes to facilitate mining and retrieval of "gold". We present a new approach for rushes structuring and indexing based on motion feature. We model the problem by a two-level Hierarchical Hidden Markov Model (HHMM). The HHMM, on one hand, represents the semantic concepts in its higher level to provide simultaneous structuring and indexing, on the other hand, models the motion feature distributions in its lower level to support the encoding of the semantic concepts. The encouraging experimental results on TRECVID'05 BBC rushes demonstrate the effectiveness of our approach.

Keywords

Motion pictures, metadata, Hierarchical Hidden Markov Model

Discipline

Databases and Information Systems | Graphics and Human Computer Interfaces

Research Areas

Intelligent Systems and Optimization

Publication

Image and Video Retrieval: 5th International Conference on Image and Video Retrieval, CIVR 2006, Tempe, AZ, July 13-15: Proceedings

Volume

4071

First Page

241

Last Page

250

ISBN

9783540360186

Identifier

10.1007/11788034_25

Publisher

Springer

City or Country

Cham

Additional URL

https://doi.org/10.1007/11788034_25

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