Paper
27 December 1999 Content-based scene change detection and classification technique using background tracking
Author Affiliations +
Proceedings Volume 3969, Multimedia Computing and Networking 2000; (1999) https://doi.org/10.1117/12.373529
Event: Electronic Imaging, 2000, San Jose, CA, United States
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.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
JungHwan Oh, Kien A. Hua, and Ning Liang "Content-based scene change detection and classification technique using background tracking", Proc. SPIE 3969, Multimedia Computing and Networking 2000, (27 December 1999); https://doi.org/10.1117/12.373529
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CITATIONS
Cited by 29 scholarly publications.
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KEYWORDS
Video

Cameras

Databases

Scene classification

Video compression

Data processing

Semantic video

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