Multimedia Tools and Applications

, Volume 76, Issue 1, pp 1055–1071 | Cite as

A near-duplicate 3D video detection algorithm by using hypercomplex representations

  • Ziqiang Sun
  • Yuesheng Zhu
  • Xiaomei Xing
  • Guibo Luo
  • Xiyao Liu


Copyright protection is still a crucial open issue in the 3D video industry with the development of 3DTV coupled with the increasing 3D video spread over the internet. In this paper a novel video fingerprinting is proposed for near-duplicate 3D video detection. Instead of generating fingerprints from the color frames and the depth maps separately, the proposed algorithm processes them in a holistic manner. The hypercomplex representation developed from the RGB and depth components is used to represent the 3D contents as quaternion frames and a novel quaternion centroid of the spatio-temporal gradient orientations is exploited to generate 3D video fingerprints based on these quaternion frames. Comprehensive experiments are conducted to evaluate the performance of the proposed method, and the results show that the proposed near-duplicate 3D video detection algorithm outperforms the state-of-the-art approaches in terms of robustness and discrimination. And the proposed fingerprints are also more compact than the existing approaches.


Near-duplicate 3D video detection Video fingerprint Quaternion Hypercomplex representation 



This work was supported by Shenzhen Engineering Laboratory of Broadband Wireless Network Security, the Science and Technology Development Fund of Macao SARFDCT056/2012/A2, UM Multi-year Research Grant MYRG144 (Y1-L2) - FST11 - ZLM, and the Next Generation of Information Technology Industry Development Special Fund of Shenzhen XXH-YY20130329010018.


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Ziqiang Sun
    • 1
  • Yuesheng Zhu
    • 1
  • Xiaomei Xing
    • 1
  • Guibo Luo
    • 1
  • Xiyao Liu
    • 1
  1. 1.Communication & Information Security Lab, Institute of Big Data Technologies, Shenzhen Graduate SchoolPeking UniversityBeijingChina

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