Title

Content-Based Scene Change Detection And Classification Technique Using Background Tracking

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.

Publication Date

1-1-2000

Publication Title

Proceedings of SPIE - The International Society for Optical Engineering

Volume

3969

Number of Pages

254-265

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

0033878179 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0033878179

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