Abstract
Video copy detection has found wide applications in digital multimedia forensics and copyright protection. With video copy detection, one can not only determine the presence of a query video in the massive video database, but also locate it precisely. This paper presents an effective video copy detection scheme based on the statistics of quantized Zernike moments. In our approach, each video frame is partitioned into non-overlapping blocks. The Zernike moments of first few orders are then calculated for each block. Finally, the frame-level feature is generated by aggregating statistics of the quantized Zernike moments of all the blocks in the video frame. Through extensive experiments on a public video database, this frame-level feature is demonstrated to be robust against geometric transformation, color adjustment, noise contamination and many other commonly used content-preserving operations. Compared with existing schemes in the literatures, the proposed method yields better or at least comparable performance in a series of experiments.
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References
Lee, S.J., Jung, S.H.: A survey of watermarking techniques applied to multimedia. In: Proceedings ISIE, Industrial Electronics, vol. 1, pp. 272–277 (2001)
Hampapur, A., Bolle, R.M.: Comparison of distance measures for video copy detection. In: Proceedings of the 2001 IEEE International Conference on Multimedia and Expo (ICME), pp. 737–740 (2001)
Mohan, R.: Video sequence matching. In: Proceedings of the 1998 IEEE International Conference on Speech and Signal Processing, vol. 6, pp. 3697–3700 (1998)
Kim, C., Vasudev, B.: Spatiotemporal sequence matching for efficient video copy detection. IEEE Trans. Circuits Syst. Video Technol. 15(1), 127–132 (2005)
Chen, L., Stentiford, F.W.M.: Video sequence matching based on temporal ordinal measurement. Pattern Recogn. Lett. 29(13), 1824–1831 (2008)
Swain, M.J., Ballard, D.H.: Color indexing. Int. J. Comput. Vis. 7(1), 11–32 (1991)
Lei, Y.Q., Luo, W.Q., Wang, Y.G., Huang, J.W.: Video sequence matching based on the invariance of color correlation. IEEE Trans. Circuits Syst. Video Technol. 22(9), 1332–1343 (2012)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60(2), 91–110 (2004)
Maani, E., Tsaftaris, S.A., Katsaggelos, A.K.: Local feature extraction for video copy detection in a database. In: Proceedings of 15th IEEE International Conference on Image Processing, pp. 1716–1719 (2008)
Liu, Z., Liu, T., Gibbon, D.C., Shahraray, B.: Effective and scalable video copy detection. In: Proceedings of the 2010 International Conference on Multimedia Information Retrieval, pp. 119–128 (2010)
Teague, M.R.: Image analysis via the general theory of moments. J. Opt. Soc. Am. 70(8), 920–930 (1980)
Zheng, L.G., Qiu, G.P., Huang, J.W., Fu, H.: Salient covariance for near-duplicate image and video detection. In: Proceedings of 18th IEEE International Conference on Image Processing, pp. 2537–2540 (2011)
Zheng, L.G., Lei, Y.Q., Qiu, G.P., Huang, J.W.: Near-duplicate image detection in a visually salient riemannian space. IEEE Trans. Inf. Forensics Secur. 7(5), 1578–1593 (2012)
Law-To, J., Joly, A., Boujemaa, N.: Muscle-VCD-2007: a live benchmark for video copy detection. http://www-rocq.inria.fr/imedia/civr-bench
Acknowledgments
This work is supported by the National Natural Science Foundation of China (61379156), the National Research Foundation for the Doctoral Program of Higher Education of China (20120171110037), and the key Program of Natural Science Foundation of Guangdong (S2012020011114).
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Chen, J., Chen, C., Ni, J. (2014). Effective Video Copy Detection Using Statistics of Quantized Zernike Moments. In: Shi, Y., Kim, HJ., Pérez-González, F. (eds) Digital-Forensics and Watermarking. IWDW 2013. Lecture Notes in Computer Science(), vol 8389. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43886-2_17
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DOI: https://doi.org/10.1007/978-3-662-43886-2_17
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