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Automatically learning structural units in educational videos with the hierarchical hidden Markov models

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conference contribution
posted on 2004-01-01, 00:00 authored by Quoc-Dinh Phung, Svetha VenkateshSvetha Venkatesh, H Bui
In this paper we present a coherent approach using the hierarchical HMM with shared structures to extract the structural units that form the building blocks of an education/training video. Rather than using hand-crafted approaches to define the structural units, we use the data from nine training videos to learn the parameters of the HHMM, and thus naturally extract the hierarchy. We then study this hierarchy and examine the nature of the structure at different levels of abstraction. Since the observable is continuous, we also show how to extend the parameter learning in the HHMM to deal with continuous observations.

History

Pagination

1605 - 1608

Location

Singapore

Open access

  • Yes

Start date

2004-10-24

End date

2004-10-27

ISSN

1522-4880

ISBN-13

9780780385542

ISBN-10

0780385543

Language

eng

Notes

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Publication classification

E1.1 Full written paper - refereed

Copyright notice

2004, IEEE

Title of proceedings

ICIP 2004 : Proceedings of the 2004 International Conference on Image Processing