Content-based video abstraction

Bilge Gunsel*, A. Murat Tekalp

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

57 Citations (Scopus)

Abstract

This paper addresses automatic scene change detection, key-frame selection, and similarity ranking which constitute the main steps of a content-based video abstraction system. Unlike other methods, the proposed algorithm performs scene change detection and key-frame selection in one step. We treat scene change detection as a two-class classification problem and employ automatic threshold selection techniques originally developed for image binarization. A quantitative measure for retrieval of similar scenes according to their color content is also defined. The described scheme can be applied to both uncompressed and MPEG compressed video, and can be implemented in real-time. Performance of the algorithm has been analyzed on real TV sequences, and comparison with some previously introduced techniques are provided.

Original languageEnglish
Pages128-132
Number of pages5
Publication statusPublished - 1998
Externally publishedYes
EventProceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3) - Chicago, IL, USA
Duration: 4 Oct 19987 Oct 1998

Conference

ConferenceProceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3)
CityChicago, IL, USA
Period4/10/987/10/98

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