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Near-Duplicate Web Video Retrieval and Localization Using Improved Edit Distance

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Web Technologies and Applications (APWeb 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9931))

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Abstract

With the development of network, there exists many near-duplicate videos online shared by individuals. These ones cause problems such as copyright infringement and search result redundancy. To solve the issues, this paper proposes a filter-and-refine framework for near-duplicate video retrieval and localization. By regarding video sequences as strings, Edit distance is used and improved in the approach. Firstly, bag-of-words (BOW) model is utilized to measure the similarities between frames. Then, non-near-duplicate videos are filtered out by computing the proposed relative Edit distance similarity (REDS). Next, a dynamic programming strategy is proposed to rank the remained videos and localize the similar segments. Experiments demonstrate the effectiveness and robustness of the method in retrieval and localization.

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References

  1. Arandjelović, R., Zisserman, A.: Three things everyone should know to improve object retrieval. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2911–2918 (2012)

    Google Scholar 

  2. Awad, G., Over, P., Kraaij, W.: Content-based video copy detection benchmarking at TRECVID. ACM Trans. Inf. Syst. (TOIS) 32(3), 14 (2014)

    Article  Google Scholar 

  3. Chiu, C.Y., Chen, C.S., Chien, L.F.: A framework for handling spatiotemporal variations in video copy detection. IEEE Trans. Circ. Syst. Video Technol. 18(3), 412–417 (2008)

    Article  Google Scholar 

  4. Chou, C.L., Chen, H.T., Lee, S.Y.: Pattern-based near-duplicate video retrieval and localization on web-scale videos. IEEE Trans. Multimedia 17(3), 382–395 (2015)

    Article  Google Scholar 

  5. Esmaeili, M.M., Fatourechi, M., Ward, R.K.: A robust and fast video copy detection system using content-based fingerprinting. IEEE Trans. Inf. Forensics Secur. 6(1), 213–226 (2011)

    Article  Google Scholar 

  6. Huang, Z., Shen, H.T., Shao, J., Zhou, X., Cui, B.: Bounded coordinate system indexing for real-time video clip search. ACM Trans. Inf. Syst. (TOIS) 27(3), 17 (2009)

    Article  Google Scholar 

  7. Jegou, H., Douze, M., Schmid, C.: Hamming embedding and weak geometric consistency for large scale image search. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part I. LNCS, vol. 5302, pp. 304–317. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  8. Kraaij, W., Awad, G.: TRECVID 2011 content-based copy detection: task overview. In: Online Proceedings of TRECVID (2011)

    Google Scholar 

  9. Liu, J., Huang, Z., Cai, H., Shen, H.T., Ngo, C.W., Wang, W.: Near-duplicate video retrieval: current research and future trends. ACM Compu. Surv. (CSUR) 45(4), 44 (2013)

    Google Scholar 

  10. Liu, L., Lai, W., Hua, X.-S., Yang, S.-Q.: Video histogram: a novel video signature for efficient web video duplicate detection. In: Cham, T.-J., Cai, J., Dorai, C., Rajan, D., Chua, T.-S., Chia, L.-T. (eds.) MMM 2007. LNCS, vol. 4352, pp. 94–103. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  11. Roopalakshmi, R., Reddy, G.R.M.: A novel spatio-temporal registration framework for video copy localization based on multimodal features. Signal Process. 93(8), 2339–2351 (2013)

    Article  Google Scholar 

  12. Song, J., Yang, Y., Huang, Z., Shen, H.T., Luo, J.: Effective multiple feature hashing for large-scale near-duplicate video retrieval. IEEE Trans. Multimedia 15(8), 1997–2008 (2013)

    Article  Google Scholar 

  13. Wang, J., Shen, H.T., Song, J., Ji, J.: Hashing for similarity search: a survey. CoRR abs/1408.2927 (2014). http://arxiv.org/abs/1408.2927

  14. Wu, X., Hauptmann, A.G., Ngo, C.W.: Practical elimination of near-duplicates from web video search. In: Proceedings of the 15th International Conference on Multimedia, pp. 218–227. ACM (2007)

    Google Scholar 

  15. Wu, X., Ngo, C.W., Hauptmann, A.G., Tan, H.K.: Real-time near-duplicate elimination for web video search with content and context. IEEE Trans. Multimedia 11(2), 196–207 (2009)

    Article  Google Scholar 

  16. Yeh, M.C., Cheng, K.T.: Video copy detection by fast sequence matching. In: Proceedings of the ACM International Conference on Image and Video Retrieval, p. 45. ACM (2009)

    Google Scholar 

  17. Zhao, W.L., Wu, X., Ngo, C.W.: On the annotation of web videos by efficient near-duplicate search. IEEE Trans. Multimedia 12(5), 448–461 (2010)

    Article  Google Scholar 

Download references

Acknowledgement

This work is supported by the National Science Foundation of China (No. 61175096) and Specialized Fund for Joint Building Program of Beijing Municipal Education Commission.

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Authors and Affiliations

  1. Beijing Key Lab of Intelligent Information Technology, School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China

    Hao Liu, Qingjie Zhao, Hao Wang & Cong Zhang

Authors
  1. Hao Liu
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  2. Qingjie Zhao
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  3. Hao Wang
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  4. Cong Zhang
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Corresponding author

Correspondence to Hao Liu .

Editor information

Editors and Affiliations

  1. School of Computing, University of Utah, Salt Lake City, Utah, USA

    Feifei Li

  2. School of Electrical Engineering, Seoul National University, Seoul, Korea (Republic of)

    Kyuseok Shim

  3. Soochow University , Suzhou, China

    Kai Zheng

  4. Soochow University , Suzhou, China

    Guanfeng Liu

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© 2016 Springer International Publishing Switzerland

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Liu, H., Zhao, Q., Wang, H., Zhang, C. (2016). Near-Duplicate Web Video Retrieval and Localization Using Improved Edit Distance. In: Li, F., Shim, K., Zheng, K., Liu, G. (eds) Web Technologies and Applications. APWeb 2016. Lecture Notes in Computer Science(), vol 9931. Springer, Cham. https://doi.org/10.1007/978-3-319-45814-4_12

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  • DOI: https://doi.org/10.1007/978-3-319-45814-4_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45813-7

  • Online ISBN: 978-3-319-45814-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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