NDLI: A hidden Markov model approach to the structure of documentaries

Content Provider	IEEE Xplore Digital Library
Author	Tiecheng Liu Kender, J.R.
Copyright Year	2000
Description	Author affiliation: Dept. of Comput. Sci., Columbia Univ., New York, NY, USA (Tiecheng Liu)
Abstract	We have hand-segmented two very long documentaries (100 minutes total) into their component shots. As with other extended videos, shot distribution again appears to be log-normal. Shot lengths are similar to those in dramas, comedies, or action films, but much shorter than those in home videos. The use of fades appears to be an important device to signal transitions between semantic units. We have sought evidence for shot composition rules by means of hidden Markov models (HMMs). We find that camera motion (tilt, pan, zoom) is not significantly governed by rules. However, the bulk of the documentaries take the form of an alternation between commentators and several types of primary supporting material; additionally, the documentaries end with a visual summary. We find that the best approach is one that trains the HMM with labeled subsequences that have approximately equal elapsed time, rather than subsequences with an equal number of shots, or subsequences with shots aligned to some semantic event. This may reflect fundamental temporal limits on human visual attention. We propose that such an underlying structure can suggest more human-sensitive designs for the analysis and graphic display of the contents of extended videos, for summarization, browsing and indexing.
Starting Page	111
Ending Page	115
File Size	1940330
Page Count	5
File Format	PDF
ISBN	076950695X
DOI	10.1109/IVL.2000.853850
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-06-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Video signal processing
Content Type	Text
Resource Type	Article

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