A Computationally Efficient Algorithm for Large Scale Near-Duplicate Video Detection

  • Dawei Liu
  • Zhihua Yu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8936)


Large scale near-duplicate video detection is very desirable for web video processing, especially the computational efficiency is essential for practical applications. In this paper, we present a computationally efficient algorithm based on multi-layer video content analysis. Local features are extracted from key frames of videos and indexed by an novel adaptive locality sensitive hashing scheme. By learning several parameters, fast retrieval in the new hashing structure is performed without high dimensional distance computations and achieves better real-time retrieving performance compared with other state-of-the-art approaches. Then a descriptor filtering method and a two-level matching scheme is performed to generate a relevance score for detection. Experiments on near-duplicate video detection tasks including various transformed videos demonstrate the efficiency gains of the proposed algorithm.


Near-duplicate Detection Locality sensitive hashing SURF Multimedia content analysis 


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  1. 1.
    Zhang, Z., Cao, C., Zhang, R., Zou, J.: Video Copy Detection Based on Speeded Up Robust Features and Locality Sensitive Hashing. In: Proc. IEEE Int. Conf. Automation and Logistics, pp. 13–18 (2010)Google Scholar
  2. 2.
    Bay, H., Tuytelaars, T., Van Gool, L.: Speeded-up Robust Features (SURF). Comput. Vis. Image Underst. 3(110), 404–417 (2008)Google Scholar
  3. 3.
    Gionis, A., Indyk, P., Motwani, R.: Similarity Search in High Dimensions via Hashing. In: Proc. Int. Conf. Very Large Data Bases, pp. 518–529 (1999)Google Scholar
  4. 4.
    Datar, M., Immorlica, N., Indyk, P., Mirrokni, V.: Locality-sensitive hashing Scheme Based on p-stable Distributions. In: Proc. ACM Symposium on Computational Geometry (2004)Google Scholar
  5. 5.
    Yeh, M., Cheng, K.-T.: Fast Visual Retrieval Using Accelerated Sequence Matching. IEEE Trans. Multimedia 13(2), 320–329 (2011)CrossRefGoogle Scholar
  6. 6.
    Yeh, M., Cheng, K.T.: A Compact, Effective Descriptor for Video Copy Detection. In: Proc. ACM Int. Conf. Multimedia, pp. 633–636 (2009)Google Scholar
  7. 7.
    Caspi, Y., Irani, M.: Spatio-Temporal Alignment of Sequences. IEEE Trans. Pattern Anal. Mach. Intell. 24(11), 1409–1424 (2002)CrossRefGoogle Scholar
  8. 8.
    Shang, L., Yang, L., Wang, F., Chan, K., Hua, X.: Real-time Large Scale Near-duplicate Web Video Retrieval. In: Proc. ACM Int. Conf. Multimedia, pp. 531–540 (2010)Google Scholar
  9. 9.
    Liu, X., Liu, T., Gibbon, D., Shahraray, B.: Effective and Scalable Video Copy Detection. In: Proc. ACM Int. Conf. Multimedia Information Retrieval, pp. 119–128 (2010)Google Scholar
  10. 10.
    Law-To, J., Chen, L., Joly, A., Laptev, I., Buisson, O., Gouet-Brunet, V., Boujemaa, N., Stentiford, F.: Video Copy Detection: A Comparative Study. In: Proc. ACM Int. Conf. Image and Video Retrieval (2007)Google Scholar
  11. 11.
    Kim, C., Vasudev, B.: Spatiotemporal Sequence Matching for Efficient Video Copy Detection. IEEE Trans. Circuits Syst. Video Technol. 15(1), 127–132 (2005)CrossRefGoogle Scholar
  12. 12.
    Avrithis, Y., Tolias, G., Kalantidis, Y.: Feature Map Hashing: Sub-linear Indexing of Appearance and Global Geometry. In: Proc. ACM Int. Conf. Multimedia, pp. 231–240 (2010)Google Scholar
  13. 13.
    Chiu, C., Wang, H., Chen, C.: Fast Min-hashing Indexing and Robust Spatio-temporal Matching for Detection Video Copies. ACM Trans. Multimed. Comput. Comm. Appl. 6(2), Article 10 (2010)Google Scholar
  14. 14.
    Poullot, S., Buisson, O., Crucianu, M.: Scaling Content-based Video Copy Detection to Very Large Databases. Multimed. Tools Appl. 47, 279–306 (2010)CrossRefGoogle Scholar
  15. 15.
    Law-To, J., Joly, A., Boujemaa, N.: Muscle-VCD-2007: A Live Benchmark for Video Copy Detection (2007)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Dawei Liu
    • 1
  • Zhihua Yu
    • 1
    • 2
  1. 1.Instititue of Network Technology, Institute of Computing Technology(Yantai)CASShandongP.R. China
  2. 2.Instititue of Computing TechnologyCASBeijingP.R. China

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