Skip to main content

Research on Shot Detection Algorithm of Self-adaptive Dual Thresholds Based on Multi-feature Fusion

  • Chapter
  • First Online:
Transactions on Edutainment XIII

Part of the book series: Lecture Notes in Computer Science ((TEDUTAIN,volume 10092))

Abstract

The shot is basic physical unit of video sequence, which is a collection of several consecutive frames in time and space that is captured by a camera. Shot boundary detection is the structural basis of video retrieval, the performance of detection algorithm will directly affect the efficiency of video retrieval. By describing and analyzing advantages and disadvantages of existing algorithms, this paper proposes a shot detection algorithm of self-adaptive dual thresholds based on multi-feature fusion. Firstly, frame difference is calculated by combining HSV color feature and LBP texture feature in the image that is non-uniformly divided into several blocks. Secondly, frame difference is compared with two self-adaptive thresholds to detect shot boundary. Finally, video is segmented some independent shots. Experiment analysis shows that this algorithm can’t only extract features that reflect main contents of video images, but also effectively detect abrupt shots and gradual shots. It reduces the number of false detection and miss detection, therefore, it has higher recall and precision than existing shot boundary detection algorithms. To a certain extent, this algorithm improves the efficiency of shot boundary detection.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Wang, S., Jia, K., Wang, C., Liu, W.: Abrupt cut detection and key frame extraction based on motion information. Comput. Eng. 16, 5–8 (2012)

    Google Scholar 

  2. Liu, G., Wen, X., Zheng, W., et al.: Shot boundary detection and keyframe extraction based on scale invariant feature transform. In: Eigth IEEE/ACIS International Conference on Computer and Information Science, pp. 1126–1130. IEEE Computer Society (2009)

    Google Scholar 

  3. Wei, M.: The Research of the Key Frame Extraction Algorithm of Content-based Video Retrieval. Wuhan Polytechnic University (2010)

    Google Scholar 

  4. Quandong, L.: Content-Based Video Retrieval Research on Shot Detection and Key Frame Extraction. North University of China (2011)

    Google Scholar 

  5. Feng, H., Yuan, X., Wei, M., et al.: A shot boundary detection method based on color space. In: Proceedings of the International Conference on E-Business and E-Government, ICEE 2010, 7–9 May 2010, Guangzhou, China, pp. 1647–1650 (2010)

    Google Scholar 

  6. Quanlei, H.: Research on Content-based Video Shot Segmentation and Retrieval Technology. Shandong University (2009)

    Google Scholar 

  7. Quintyne, K.I., Walsh, L., Coate, L.: A self-adapting dual-threshold method for video shot transition detection. In: 2008 IEEE International Conference on Networking, Sensing and Control, ICNSC 2008, pp. 704–707 IEEE (2008)

    Google Scholar 

  8. Zhao, N., Ning, L., Liu, H.Y.: Content-based cut shot detecting algorithm of news video. J. Jilin Univ. (2009)

    Google Scholar 

  9. Zhang, M.: The Research on Key Frame Selection and Feature Matching Video Retrieval. Beijing University of Posts and Telecommunications (2012)

    Google Scholar 

  10. Ekin, A., Tekalp, A.M.: Automatic soccer video analysis and summarization. IEEE Trans. Image Process. 12(7), 796–807 (2003)

    Article  Google Scholar 

  11. Lu, Z.M., Shi, Y.: Fast video shot boundary detection based on SVD and pattern matching. IEEE Trans. Image Process. 22(12), 5136–5145 (2013). A Publication of the IEEE Signal Processing Society

    Article  MathSciNet  Google Scholar 

  12. Miao, P.: Research on Some Technologies Based on Video Retrieval. Nanjing University of Science and Technology (2010)

    Google Scholar 

  13. Liu, X.: Research on Key Frame Extraction Algorithm Based on Multi-feature in Video Retrieval. China University of Mining and Technology (2015)

    Google Scholar 

  14. Zhou, L.: Research of Shot Detection and Key Frame Extraction of Content-based Video Retrieval. Hebei University of Technology (2014)

    Google Scholar 

  15. Tang, J., Xie, L., Yuan, Q., et al.: Shot boundary detection algorithm based on ORB. J. Commun. 11, 187–190 (2013)

    Google Scholar 

  16. Li, D., Jin, L., Yang, W., Fei, M.: Shot boundary detection algorithm based on self-adaptive dual thresholds of accumulative frame. Comput. Sci. 39(6), 258–260+296 (2012)

    Google Scholar 

Download references

Acknowledgments

Science and technology project of Shanxi Province in 2013(20130321007-02).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jinlai Lv .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer-Verlag GmbH Germany

About this chapter

Cite this chapter

Lv, J., Bai, H. (2017). Research on Shot Detection Algorithm of Self-adaptive Dual Thresholds Based on Multi-feature Fusion. In: Pan, Z., Cheok, A., MĂĽller, W., Zhang, M. (eds) Transactions on Edutainment XIII. Lecture Notes in Computer Science(), vol 10092. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-54395-5_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-54395-5_21

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-54394-8

  • Online ISBN: 978-3-662-54395-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics