Skip to main content

Revisiting SIRET Video Retrieval Tool

  • Conference paper
  • First Online:
MultiMedia Modeling (MMM 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10705))

Included in the following conference series:

Abstract

The known-item and ad-hoc video search tasks still represent challenging problems for the video retrieval community. During last years, the Video Browser Showdown identified several promising approaches that can improve the effectiveness of interactive video retrieval tools focusing on the tasks. We present a major revision of the SIRET interactive video retrieval tool that follows these findings. The new version employs three different query initialization approaches and provides several result visualization methods for effective navigation and browsing in sets of ranked keyframes.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Only the supported set of labels L of a selected model M can be used to form the query (our UI keyword search element prompts the labels).

References

  1. Amato, G., Falchi, F., Gennaro, C., Rabitti, F.: Searching and annotating 100M images with YFCC100M-HNFC6 and MI-file. In: Proceedings of the 15th International Workshop on Content-Based Multimedia Indexing, CBMI 2017, New York, NY, USA, pp. 26:1–26:4. ACM (2017)

    Google Scholar 

  2. Awad, G., Butt, A., Fiscus, J., Michel, M., Joy, D., Kraaij, W., Smeaton, A.F., Quénot, G., Eskevich, M., Ordelman, R., Jones, G.J.F., Huet, B.: TRECVID 2017: evaluating ad-hoc and instance video search, events detection, video captioning and hyperlinking. In: Proceedings of TRECVID 2017. NIST (2017)

    Google Scholar 

  3. Barthel, K.U., Hezel, N., Mackowiak, R.: Navigating a graph of scenes for exploring large video collections. In: Tian, Q., Sebe, N., Qi, G.-J., Huet, B., Hong, R., Liu, X. (eds.) MMM 2016. LNCS, vol. 9517, pp. 418–423. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-27674-8_43

    Chapter  Google Scholar 

  4. Blaz̆ek, A., Lokoc̆, J., Kubon̆, D.: Video hunter at VBS 2017. In: Amsaleg, L., Guðmundsson, G.Þ., Gurrin, C., Jónsson, B.Þ., Satoh, S. (eds.) MMM 2017. LNCS, vol. 10133, pp. 493–498. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-51814-5_47

    Chapter  Google Scholar 

  5. Blažek, A., Lokoč, J., Skopal, T.: Video retrieval with feature signature sketches. In: Traina, A.J.M., Traina, C., Cordeiro, R.L.F. (eds.) SISAP 2014. LNCS, vol. 8821, pp. 25–36. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-11988-5_3

    Google Scholar 

  6. Budíková, P., Batko, M., Zezula, P.: Fusion strategies for large-scale multi-modal image retrieval. Ttans. Large-Scale Data Knowl.-Centered Syst. 33, 146–184 (2017)

    Google Scholar 

  7. Cobârzan, C., Schoeffmann, K., Bailer, W., Hürst, W., Blažek, A., Lokoč, J., Vrochidis, S., Barthel, K.U., Rossetto, L.: Interactive video search tools: a detailed analysis of the video browser showdown 2015. Multimed. Tools Appl. 76(4), 5539–5571 (2016)

    Article  Google Scholar 

  8. Lokoč, J., Blažek, A., Skopal, T.: Signature-based video browser. In: Gurrin, C., Hopfgartner, F., Hurst, W., Johansen, H., Lee, H., O’Connor, N. (eds.) MMM 2014. LNCS, vol. 8326, pp. 415–418. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-04117-9_49

    Chapter  Google Scholar 

  9. Lokoč, J., Phuong, A.N., Vomlelová, M., Ngo, C.-W.: Color-sketch simulator: a guide for color-based visual known-item search. In: Cong, G., Peng, W.-C., Zhang, W.E., Li, C., Sun, A. (eds.) ADMA 2017. LNCS (LNAI), vol. 10604, pp. 754–763. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-69179-4_53

    Chapter  Google Scholar 

  10. Rossetto, L., Giangreco, I., Tănase, C., Schuldt, H., Dupont, S., Seddati, O.: Enhanced retrieval and browsing in the IMOTION system. In: Amsaleg, L., Guðmundsson, G.Þ., Gurrin, C., Jónsson, B.Þ., Satoh, S. (eds.) MMM 2017. LNCS, vol. 10133, pp. 469–474. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-51814-5_43

    Chapter  Google Scholar 

  11. Russakovsky, O., Deng, J., Hao, S., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., Berg, A.C., Fei-Fei, L.: Imagenet large scale visual recognition challenge. Int. J. Comput. Vis. 115(3), 211–252 (2015)

    Article  MathSciNet  Google Scholar 

  12. Schoeffmann, K.: A user-centric media retrieval competition: the video browser showdown 2012–2014. IEEE Multimed. 21(4), 8–13 (2014)

    Article  Google Scholar 

  13. Schoeffmann, K., Hudelist, M.A., Huber, J.: Video interaction tools: a survey of recent work. ACM Comput. Surv. 48(1), 14 (2015)

    Article  Google Scholar 

  14. Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. CoRR, abs/1409.1556 (2014)

    Google Scholar 

  15. Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S.E., Anguelov, D., Erhan, D., Vanhoucke, V., Rabinovich, A.: Going deeper with convolutions. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015, Boston, MA, USA, 7–12 June 2015, pp. 1–9 (2015)

    Google Scholar 

Download references

Acknowledgments

This paper has been supported by Czech Science Foundation (GAČR) project Nr. 17-22224S and by grant SVV-2017-260451.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jakub Lokoč .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Lokoč, J., Kovalčík, G., Souček, T. (2018). Revisiting SIRET Video Retrieval Tool. In: Schoeffmann, K., et al. MultiMedia Modeling. MMM 2018. Lecture Notes in Computer Science(), vol 10705. Springer, Cham. https://doi.org/10.1007/978-3-319-73600-6_44

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-73600-6_44

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-73599-3

  • Online ISBN: 978-3-319-73600-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics