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High level segmentation of instructional videos based on content density
conference contribution
posted on 2002-01-01, 00:00 authored by Quoc-Dinh Phung, Svetha VenkateshSvetha Venkatesh, C DoraiAutomatically partitioning instructional videos into topic sections is a challenging problem in e-learning environments for efficient content management and cataloging. This paper addresses this problem by proposing a novel density function to delineate sections underscored by changes in topics in instructional and training videos. The content density function draws guidance from the observation that topic boundaries coincide with the ebb and flow of the 'density' of content shown in these videos. Based on this function, we propose two methods for high-level segmentation by determining topic boundaries. We study the performance of the two methods on eight training videos, and our experimental results demonstrate the effectiveness and robustness of the two proposed high-level segmentation algorithms for learning media.
History
Event
ACM International Conference on Multimedia (10th : 2002 : Juan-les-Pins, France)Pagination
295 - 298Publisher
ACMLocation
Juan-les-Pins, FrancePlace of publication
New York, N. Y.Publisher DOI
Start date
2002-12-01End date
2002-12-06ISBN-10
158113620XLanguage
engPublication classification
E1.1 Full written paper - refereedCopyright notice
2002, ACMTitle of proceedings
MULTIMEDIA 2002 : Proceedings of the 10th ACM International Multimedia Conference and ExhibitionUsage metrics
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