Skip to main content
Log in

Video fingerprinting based on graph model

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

A robust video fingerprinting based on graph model is proposed in this paper, where two graph models are constructed for key frames selection and foreground extraction, respectively. First, the video is represented as a complete undirected graph and a binary tree is formed using normalized cut algorithm to select key frames. Then, the pixels of each key frame are modeled as a Markov Random Field and another graph model is formed to extract foreground by graph cut. Finally, the fourth-order cumulant of foreground is computed to generate video fingerprints. Experimental results show that the proposed algorithm has good robustness and discrimination.

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

Access this article

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Coskun B, Sankur B, Memon N (2006) Spatio-temporal transform based video hashing. IEEE Trans Multimedia 8(6):1190–1208

    Article  Google Scholar 

  2. Esmaeili MM, Fatourechi M, Ward RK (2011) A robust and fast video copy detection system using content-based fingerprinting. IEEE Trans Info Forensics and Sec 6(1):213–216

    Article  Google Scholar 

  3. Howe NR, Deschamps A (2004) Better foreground segmentation through graph cuts. Technical Report

  4. Jeong KM, Lee J-J, Ha Y-H (2006) Video sequence matching using singular value decomposition. In: Proc. 3rd int. conf. image analysis and recognition (ICIAR), pp 426–435

  5. Kolmogorov V, Zabih R (2004) What energy functions can be minimized via graph cuts? TPAMI 26(2):147–159

    Article  Google Scholar 

  6. Lee S, Yoo CD (2006) Video fingerprinting based on centroids of gradient orientations. In: Proc. int. conf. acoust., speech and signal processing (ICASSP), vol 2, pp 401–404

  7. Maani E, Tsaftaris SA, Katsaggelos AK (2008) Local feature extraction for video copy detection in a database. In: IEEE int. conf. image proc. (ICIP), pp 1716–1719

  8. Nie XS, Liu J, Sun JD et al (2011) Robust video hashing based on double-layer embedding. IEEE Signal Process Lett 18(5):307–310

    Article  Google Scholar 

  9. Nie XS, Qiao JP (2012) Robust video copy detection approach based on local tangent space alignment. Opt Eng 51(4):047001

    Article  Google Scholar 

  10. Ngo CW, Ma YU, Zhang HJ (2005) Video summarization and scene detection by graph modeling. IEEE Trans Circuits Syst Video Technol 15(2):296–305

    Article  Google Scholar 

  11. Oostveen J, Kalker T, Haitsma J (2002) Feature extraction and a database strategy for video fingerprinting. In: Proc. 5th int. conf. recent advance in visual information systems, pp 117–128

  12. Shi J, Malik J (2000) Normalized cuts and image segmentation. IEEE Trans Pattern Anal Mach Intell 22(8):888–905

    Article  Google Scholar 

  13. Sun JD, Wang J, Zhang J et al (2012) Video hashing algorithm with weighted matching based on visual saliency. IEEE Signal Process Lett 19(6):328–331

    Article  MathSciNet  Google Scholar 

  14. Sun YD, Li B, Yuan BZ, Miao ZJ, Wang CZ (2006) Better foreground segmentation for static cameras via new energy form and dynamic graph-cut. In: The 18th international conference on pattern recognition (ICPR06), pp 49–52

  15. Tan HK, Ngo CW, Chua TS (2010) Efficient mining of multiple partial near-duplicate alignments by temporal network. IEEE Trans Circuits Syst Video Technol 20(11):1486–1498

    Article  Google Scholar 

  16. The origin of the video dataset is MUSCLE-VCD-2007. https://www.rocq.inria.fr/imedia/civrbench/benchMuscle.html

Download references

Acknowledgments

This work is supported partially by National Natural Science Foundation of China (61101162, 61001180) and Shandong province information fusion and industrialization of special research subject (2012EI025, 2012EI020). We also thanks Nicholas R. Howe for offering their matlab codes in his homepage.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xiushan Nie.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Nie, X., Sun, J., Xing, Z. et al. Video fingerprinting based on graph model. Multimed Tools Appl 69, 429–442 (2014). https://doi.org/10.1007/s11042-012-1341-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-012-1341-4

Keywords

Navigation