Skip to main content
SpringerLink
Log in

A Domain Independent Approach to Video Summarization

  • Conference paper
  • First Online:
Advanced Concepts for Intelligent Vision Systems (ACIVS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10617))

Abstract

With the increase in media streaming content and consumer-level video creation, there is a high demand for automatic video summarization systems. This paper proposes a bottom-up approach for the automatic generation of dynamic video summaries. Our approach integrates motion and saliency analysis with temporal slicing to extract features from the video, and to further find candidate shots. A shot similarity measure is proposed for constructing the dynamic summaries for candidate shots. From a practical perspective, our main contribution is the design of a video summarization system that is independent on the video domain. We show that the system performs equally well for domains at the extreme opposites of the domain spectrum, namely professionally edited videos and egocentric videos, without any prior information on the video contents.

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

Access this chapter

Log in via an institution
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. Birchfield, S.T., Rangarajan, S.: Spatiograms versus histograms for region-based tracking. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, vol. 2, pp. 1158–1163. IEEE (2005)

    Google Scholar 

  2. Bobick, A.F., Davis, J.W.: The recognition of human movement using temporal templates. IEEE Trans. Pattern Anal. Mach. Intell. 23(3), 257–267 (2001)

    Article  Google Scholar 

  3. Conaire, C.O., O’Connor, N.E., Smeaton, A.F.: An improved spatiogram similarity measure for robust object localisation. In: IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2007, vol. 1, pp. I-1069. IEEE (2007)

    Google Scholar 

  4. Ejaz, N., Tariq, T.B., Baik, S.W.: Adaptive key frame extraction for video summarization using an aggregation mechanism. J. Vis. Commun. Image Represent. 23(7), 1031–1040 (2012)

    Article  Google Scholar 

  5. Ghosh, J., Lee, Y.J., Grauman, K.: Discovering important people and objects for egocentric video summarization. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1346–1353. IEEE (2012)

    Google Scholar 

  6. Hou, X., Zhang, L.: Saliency detection: a spectral residual approach. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2007, pp. 1–8. IEEE (2007)

    Google Scholar 

  7. Lin, C.Y.: Rouge: a package for automatic evaluation of summaries. In: Text Summarization Branches Out: Proceedings of the ACL-04 Workshop, vol. 8 (2004)

    Google Scholar 

  8. Lu, Z., Grauman, K.: Story-driven summarization for egocentric video. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2714–2721. IEEE (2013)

    Google Scholar 

  9. Ngo, C.W., Pong, T.C., Chin, R.T.: Detection of gradual transitions through temporal slice analysis. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1. IEEE (1999)

    Google Scholar 

  10. Over, P., Smeaton, A.F., Awad, G.: The trecvid 2008 BBC rushes summarization evaluation. In: Proceedings of the 2nd ACM TRECVid Video Summarization Workshop, pp. 1–20. ACM (2008)

    Google Scholar 

  11. Petersohn, C.: Sub-shots-basic units of video. In: 14th International Workshop on Systems, Signals and Image Processing, 2007 and 6th EURASIP Conference Focused on Speech and Image Processing, Multimedia Communications and Services, pp. 323–326. IEEE (2007)

    Google Scholar 

  12. Xiang, T., Gong, S., Parkinson, D.: Autonomous visual events detection and classification without explicit object-centred segmentation and tracking. In: BMVC, pp. 1–10. Citeseer (2002)

    Google Scholar 

  13. Yeung, S., Fathi, A., Fei-Fei, L.: Videoset: video summary evaluation through text. arXiv preprint arXiv:1406.5824 (2014)

  14. Zivkovic, Z.: Improved adaptive Gaussian mixture model for background subtraction. In: Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004, vol. 2, pp. 28–31. IEEE (2004)

    Google Scholar 

  15. Zivkovic, Z., van der Heijden, F.: Efficient adaptive density estimation per image pixel for the task of background subtraction. Pattern Recogn. Lett. 27(7), 773–780 (2006)

    Article  Google Scholar 

Download references

Acknowledgments

The authors thank Dr. Cote for her useful comments on the paper, and Dr. Jean for his open source implementation of spatiograms.

Author information

Authors and Affiliations

  1. Electrical and Computer Engineering, University of Victoria, Victoria, BC, Canada

    Amanda Dash & Alexandra Branzan Albu

Authors
  1. Amanda Dash
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alexandra Branzan Albu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alexandra Branzan Albu .

Editor information

Editors and Affiliations

  1. DGA, Paris, France

    Jacques Blanc-Talon

  2. University of Antwerp, Antwerp, Belgium

    Rudi Penne

  3. Ghent University - imec, Ghent, Belgium

    Wilfried Philips

  4. CSIRO Data 61, Canberra, Aust Capital Terr, Australia

    Dan Popescu

  5. University of Antwerp, Wilrijk, Belgium

    Paul Scheunders

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Dash, A., Albu, A.B. (2017). A Domain Independent Approach to Video Summarization. In: Blanc-Talon, J., Penne, R., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2017. Lecture Notes in Computer Science(), vol 10617. Springer, Cham. https://doi.org/10.1007/978-3-319-70353-4_37

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-70353-4_37

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70352-7

  • Online ISBN: 978-3-319-70353-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation