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Proceedings Paper

Content-based scene change detection and classification technique using background tracking
Author(s): JungHwan Oh; Kien A. Hua; Ning Liang
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Paper Abstract

Scene is considered a good unit for indexing and retrieving data from large video databases. In this paper, we present a new content-based approach for detecting and classifying scene changes in video sequences. Our technique can detect and classify not only abrupt changes (i.e., hard cuts) but also gradual changes such as fades and dissolves. We compute background difference between frames, and use background tracking to handle various camera motions. Although our method processes significantly less data, it results in more semantically rich pieces (i.e., scenes). Our experiments on various types of videos indicate that the proposed technique is much less sensitive to the predefined threshold values, and is very effective in reducing the number of false hits. Our approach is particularly suitable for very large video databases because it is both space and time efficient.

Paper Details

Date Published: 27 December 1999
PDF: 12 pages
Proc. SPIE 3969, Multimedia Computing and Networking 2000, (27 December 1999); doi: 10.1117/12.373529
Show Author Affiliations
JungHwan Oh, Univ. of Central Florida (United States)
Kien A. Hua, Univ. of Central Florida (United States)
Ning Liang, Univ. of Central Florida (United States)


Published in SPIE Proceedings Vol. 3969:
Multimedia Computing and Networking 2000
Klara Nahrstedt; Wu-chi Feng, Editor(s)

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