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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.

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Correspondence to Ali Amiri.

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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.

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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

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Keywords

  • Probability Function
  • Video Frame
  • Gradual Transition
  • Boundary Detection
  • Spatiotemporal Feature