Skip to main content
SpringerLink
Log in

Shot boundary detection in the presence of illumination and motion

  • Original Paper
  • Published:
Signal, Image and Video Processing Aims and scope Submit manuscript

Abstract

Detection of gradual transition and the elimination of disturbances caused by illumination change or fast object and camera motion are the major challenges to the current shot boundary detection techniques. These disturbances are often mistaken as shot boundaries. Therefore, it is a challenging task to develop a method that is not only insensitive to various disturbances but also sensitive enough to capture a shot change. To address these challenges, we propose an algorithm for shot boundary detection in the presence of illumination change, fast object motion, and fast camera motion. This is important for accurate and robust detection of shot boundaries and in turn critical for high-level content-based analysis of video. First, the propose algorithm extracts structure features from each video frame by using dual-tree complex wavelet transform. Then, spatial domain structure similarity is computed between adjacent frames. The declaration of shot boundaries are decided based on carefully chosen thresholds. Experimental study is performed on a number of videos that include significant illumination change and fast motion of camera and objects. The performance comparison of the proposed algorithm with other existing techniques validates its effectiveness in terms of better Recall, Precision, and F1 score.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Zhang H.J., Kankanhalli A., Smoliar S.: Automatic partitioning of full-motion video. Multimedia Systems 1(1), 10–28 (1993)

    Article  Google Scholar 

  2. Boreezky J.S., Rowe L.A.: Comparison of video shot boundary detection techniques. Proc. SPIE Storage Retr. Image Video Databases 2664(IV), 170–179 (1996)

    Google Scholar 

  3. Lienhart R.: Comparison of automatic shot boundary tetection algorithms. Proc. SPIE Image and Video Process. 3656(VII), 25–30 (1999)

    Google Scholar 

  4. Hanjalic A.: Shot boundary detection: unraveled and resolved. IEEE Trans. Circuits Syst. Video Technol. 12(2), 90–105 (2002)

    Article  Google Scholar 

  5. Gargi U., Kasturi R., Strayer S.: Performance characterization of video-shot-change detection methods. in: IEEE Trans. Circuits Syst. Video Technol. 10(1), 1–13 (2000)

    Article  Google Scholar 

  6. Ford R., Roboson C., Temple D., Gerlach M.: Metrics for shot boundary detection in digital video sequences. Multimed. Syst. 8, 37–46 (2000)

    Article  Google Scholar 

  7. Becós J., Cisneros G., Martínez J., Cabrera J.: A unified model for techniques on video-shot transition detection. in: IEEE Trans. Multimed. 7(2), 293–307 (2005)

    Article  Google Scholar 

  8. Yuan J., Wang H., Xiao L., Zheng W., Li J., Lin F., Zhang B.: A formal study of shot boundary detection. in: IEEE Trans. Circuits Syst. Video Technol. 17(2), 168–186 (2007)

    Article  Google Scholar 

  9. Li, D., Lu, H.: Avoiding false alarms due to illumination variation in shot detection. In: Proceedings of the 2000 IEEE Workshop on Signal Processing Systems, pp. 828–836 (2000)

  10. Weixin, K., Ding, X., Lu, H., Songde, M.: Improvement of shot detection using illumination invariant metric and dynamic threshold selection. In: Visual’99, LNCS, vol. 1614, pp 277–282. Springer, Berlin (1999)

  11. Truong, B.T., Venkatesh, S.: Determining dramatic intensification via flashing lights in movies. In: Proceedings of IEEE International Conference on Multimedia and Expo, pp. 60–63 (2001)

  12. Guimaraes S., Couprie M., Araujo A., Leite N.: Video segmentation based on 2D image analysis. Pattern Recognit. Lett. 24(7), 947–957 (2003)

    Article  Google Scholar 

  13. Heng W.J., Ngan K.N.: High accuracy flashlight scene determination for shot boundary detection. Signal Process. Image Commun. 18(3), 203–219 (2003)

    Article  Google Scholar 

  14. Yuliang, G., De, X.: A solution to illumination variation problems in shot detection. In: TENCON 2004, IEEE Region 10 Conference, pp. 81–84 (2004)

  15. Qian X., Liu G., Su R.: Effective fades and flashlight detection based on accumulating histogram difference. in: IEEE Trans. Circuits Syst. Video Technol. 16(10), 1245–1258 (2006)

    Article  Google Scholar 

  16. Cheol, K., Cheon, Y., Kim, G., Choi, H.: Robust scene change detection algorithm for flashlights. In: Proceedings of International Conference on Computational Science and Its Applications (ICCSA), Kuala Lumpur, Malasiya, pp. 1003–1013, 26–29 Aug 2007

  17. Su C., Liao H., Fan K., chen L.: A motion-tolerant dissolve detection algorithm. in: IEEE Trans. Multimed. 7(6), 1106–1113 (2005)

    Article  Google Scholar 

  18. Xu, Y., De, X., Tengfei, G., Aimin, W., Congyan, L.: 3-DWT based motion suppression for video shot boundary detection. In: Khosla, R., et al. (eds.) Springer-verlag, KES 2005, LNAI, vol. 3682, pp. 1204–1209 (2005)

  19. Jang, S., Kim, G., Choi, H.: Shot transition detection by compensating for global and local motions. In: Wary, L., Jin, Y. (eds.) Springer-verlag, FSKD 2005, LNAI, vol. 3614, pp. 1061–1066 (2005)

  20. Park, M., Park, R., Lee, S.: Efficient shot boundary detection for action movies using blockwise motion-based features. In: Bebis, G., et al. (eds.) Springer-verlag, ISVS 2005, LNCS, vol. 3804, pp. 478–485 (2005)

  21. Kingsbury, N.G.: The dual tree complex wavelet transform: a new technique for shift invariance and directional filters. In: Proceedings of 8th IEEE DSP Workshop, Utah, 9–12 Aug 1998

  22. Kingsbury N.G.: Image processing with complex wavelet. Phil. Trans. Royal Soc. Lond. A 357, 2543–2560 (1999)

    Article  MATH  Google Scholar 

  23. Selenick I.W.: The design of approximate Hilbert transform pairs of wavelet bases. in: IEEE Trans. Signal Process. 50(5), 1144–1152 (2002)

    Article  Google Scholar 

  24. Selenick I.W., Baraniuk R.G., Kingsbury N.G.: The dual tree complex wavelet transform. IEEE Signal Process. Mag. 2(6), 123–151 (2005)

    Article  Google Scholar 

  25. Wang Z., Bovik A.C., Sheikh H.R., Simoncelli E.P.: Image quality assessment: from error visibilty to structural similarity. in: IEEE Trans. Image Process. 13(4), 600–612 (2004)

    Article  Google Scholar 

  26. Wang Z., Simoncelli E.P.: Translation insensitive image similarity in complex wavelet domain. in: Proc. IEEE Inter. Conf. Acoust. Speech Signal Process. II, 573–576 (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Indian Institute of Technology Bombay, Mumbai, India

    Krishna K. Warhade & S. N. Merchant

  2. Indian Institute of Technology Hyderabad, Hyderabad, India

    U. B. Desai

Authors
  1. Krishna K. Warhade
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S. N. Merchant
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. U. B. Desai
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Krishna K. Warhade.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Warhade, K.K., Merchant, S.N. & Desai, U.B. Shot boundary detection in the presence of illumination and motion. SIViP 7, 581–592 (2013). https://doi.org/10.1007/s11760-011-0262-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11760-011-0262-4

Keywords

Search

Navigation