venkatesh-automaticallylearning-2004.pdf (311.96 kB)
Automatically learning structural units in educational videos with the hierarchical hidden Markov models
conference contribution
posted on 2004-01-01, 00:00 authored by Quoc-Dinh Phung, Svetha VenkateshSvetha Venkatesh, H BuiIn 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
Event
International Conference on Image Processing (2004 : Singapore)Pagination
1605 - 1608Publisher
IEEELocation
SingaporePlace of publication
Piscataway, N.J.Publisher DOI
Start date
2004-10-24End date
2004-10-27ISSN
1522-4880ISBN-13
9780780385542ISBN-10
0780385543Language
engNotes
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E1.1 Full written paper - refereedCopyright notice
2004, IEEETitle of proceedings
ICIP 2004 : Proceedings of the 2004 International Conference on Image ProcessingUsage metrics
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