Skip to main content
  • Research Article
  • Open access
  • Published:

Video Shot Boundary Detection Using QR-Decomposition and Gaussian Transition Detection

Abstract

This article explores the problem of video shot boundary detection and examines a novel shot boundary detection algorithm by using QR-decomposition and modeling of gradual transitions by Gaussian functions. Specifically, the authors attend to the challenges of detecting gradual shots and extracting appropriate spatiotemporal features that affect the ability of algorithms to efficiently detect shot boundaries. The algorithm utilizes the properties of QR-decomposition and extracts a block-wise probability function that illustrates the probability of video frames to be in shot transitions. The probability function has abrupt changes in hard cut transitions, and semi-Gaussian behavior in gradual transitions. The algorithm detects these transitions by analyzing the probability function. Finally, we will report the results of the experiments using large-scale test sets provided by the TRECVID 2006, which has assessments for hard cut and gradual shot boundary detection. These results confirm the high performance of the proposed algorithm.

Publisher note

To access the full article, please see PDF.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ali Amiri.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and permissions

About this article

Cite this article

Amiri, A., Fathy, M. Video Shot Boundary Detection Using QR-Decomposition and Gaussian Transition Detection. EURASIP J. Adv. Signal Process. 2009, 509438 (2010). https://doi.org/10.1155/2009/509438

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1155/2009/509438

Keywords