Shot Change Detection Based on the Reynolds Transport Theorem

  • C. C. Shih
  • H. R. Tyan
  • H. Y. Mark Liao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2195)


Most of the conventional gradual shot change detection algorithms are heuristics-based. Usually, a general shot transition detection algorithm which can deal with different kinds of situations may be very tedious and complicated if it is heuristics-based. Under the circumstances, a general detection algorithm which has a solid theoretic ground is always preferrable. In this paper, we propose a general shot change detection algorithm which is able to achieve the above mentioned goal. The proposed algorithm consists of two major stages: the modeling stage and the detection stage. In the modeling stage, we model a shot transition by calculating the change of color/intensity distribution corresponding to the shots before and after a transition. In the detection stage, we consider a video clip as a continuous “frame flow” and then apply the Reynolds Transport Theorem to analyze the flow change within a pre-determined control volume. Using the above mentioned methodology, the shot change detection problem becomes theoretically analytic. Experimental results have proven the superiority of the proposed method.


Video Clip Detection Stage Transition Section Transition Control Volume Change Detection Technique 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    H. Jiang, A. Helal, A. K. Elmagarmid, and A. Joshi, “Scene Change Detection Technique for Video Database systems”, Multimedia Systems, Vol. 6, pp. 186–195, 1998.CrossRefGoogle Scholar
  2. [2]
    R. M. Ford, C. Robson, D. Temple, and M. Gerlach, “Metric for Shot Boundary Detection in Digital Video Sequences”, Multimedia Systems, Vol. 8, pp. 37–46, 2000.CrossRefGoogle Scholar
  3. [3]
    H. Yu and W. Wolf, “A Hierarchical Multiresolution Video shot Transition Detection Scheme”, Computer Vision and Image Understanding, Vol. 75, Nos. 1/2, Jul./Aug., pp. 196–213, 1999.CrossRefGoogle Scholar
  4. [4]
    J. Bescos, J. M. Menendez, G. Cisneros, J. Cabrera, and J. M. Martinez, “A Unified Approach to Gradual Shot Transition Detection”, Proc. Int. Conf. on Image Processing, Vo. III, pp. 949–952,. 2000.Google Scholar
  5. [5]
    H. J. Zhang, A. Kankanhalli, and S. W. Smoliar, “Automatic Partitioning of Full-Motion Video”, ACM Multimedia Systems 1, pp. 10–28, 1997.CrossRefGoogle Scholar
  6. [6]
    I. Shames, “Mechanics of Fluids,” McGRAW-HILL Book Company, Inc., 1962.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • C. C. Shih
    • 1
  • H. R. Tyan
    • 2
  • H. Y. Mark Liao
    • 1
  1. 1.Institute of Information ScienceAcadmeia SinicaTaipeiTaiwan
  2. 2.Department of Information and Computer EngineeringChung-Yuan Christian UniversityChung-LiTaiwan

Personalised recommendations