Skip to main content

A Prototype for Anomaly Detection in Video Surveillance Context

  • Conference paper
  • First Online:
Book cover Intelligent Software Methodologies, Tools and Techniques (SoMeT 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 532))

Abstract

Security has been raised at major public buildings in the most famous and crowded cities all over the world following the terrorist attacks of the last years, the latest one at the Bardo museum in the centre of Tunis. For that reason, video surveillance systems have become more and more essential for detecting and hopefully even prevent dangerous events in public areas. In this paper, we present a prototype for anomaly detection in video surveillance context. The whole process is described, starting from the video frames captured by sensors/cameras till at the end some well-known reasoning algorithms for finding potentially dangerous activities are applied. The conducted experiments confirm the efficiency and the effectiveness achieved by our prototype.

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.

    http://www.multitel.be/~va/candela/abandon.html.

References

  1. Albanese, M., Molinaro, C., Persia, F., Picariello, A., Subrahmanian, V.S.: Discovering the Top-k unexplained sequences in time-stamped observation data. IEEE Trans. Knowl. Data Eng. (TKDE) 26(3), 577–594 (2014)

    Article  Google Scholar 

  2. Albanese, M., Molinaro, C., Persia, F., Picariello, A., Subrahmanian, V.S.: Finding unexplained activities in video. In: International Joint Conference on Artificial Intelligence (IJCAI), pp. 1628–1634 (2011)

    Google Scholar 

  3. Petersen, J.K.: Understanding Surveillance Technologies. CRC Press, Boca Raton (2001)

    MATH  Google Scholar 

  4. Collins, R., Lipton, A., Kanade, T.K.: Introduction to the special section on video surveillance. IEEE Trans. Patt. Anal. Mach. Intell. 22(8), 745–746 (2000)

    Article  Google Scholar 

  5. Regazzoni, C., Ramesh, V.: Scanning the Issue/Technology Special Issue on Video Communications, Processing, and Understanding for Third Generation Surveillance Systems, University of Genoa, Siemens Corporate Research Inc., University of Udine, IEEE (2001)

    Google Scholar 

  6. Siebel, N.T., Maybank, S.J.: Fusion of multiple tracking algorithms for robust people tracking. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002, Part IV. LNCS, vol. 2353, pp. 373–387. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  7. Siebel, N.T., Maybank, S.: The advisor visual surveillance system. In: ECCV 2004 Workshop Applications of Computer Vision (ACV 2004) (2004)

    Google Scholar 

  8. Albanese, M., Pugliese, A., Subrahmanian, V.S.: Fast activity detection: indexing for temporal stochastic automaton based activity models. IEEE Trans. Knowl. Data Eng. (TKDE) 25, 360–373 (2013)

    Article  Google Scholar 

  9. Persia, F., D’Auria, D.: An application for finding expected activities in medial context scientific databases. In: SEBD 2014, pp. 77–88 (2014)

    Google Scholar 

  10. D’Auria, D., Persia, F.: Automatic evaluation of medical doctors’ performances while using a cricothyrotomy simulator. In: IRI 2014, pp. 514–519 (2014)

    Google Scholar 

  11. D’Auria, D., Persia, F.: Discovering expected activities in medical context scientific databases. In: DATA 2014, pp. 446–453 (2014)

    Google Scholar 

  12. Dung, P., Chi-Min, O., Soo-Hyung, K., In-Seop, N., Chil-Woo, L.: Object recognition by combining binary local invariant features and color histogram. In: 2013 2nd IAPR Asian Conference on Pattern Recognition (ACPR), pp. 466–470 (2013)

    Google Scholar 

  13. Chaudhary, K., Mae, Y., Kojima, M., Arai, T.: Autonomous acquisition of generic handheld objects in unstructured environments via sequential back-tracking for object recognition. In: 2014 IEEE International Conference on Robotics and Automation (ICRA), pp. 4953–4958 (2014)

    Google Scholar 

  14. Ubukata, T., Shibata, M., Terabayashi, K., Mora, A., Kawashita, T., Masuyama, G., Umeda, K.: Fast human detection combining range image segmentation and local feature based detection. In: 22nd International Conference on Pattern Recognition (ICPR), pp. 4281–4286 (2014)

    Google Scholar 

  15. Onal, I., Kardas, K., Rezaeitabar, Y., Bayram, U., Bal, M., Ulusoy, I., Cicekli, N.K.: A framework for detecting complex events in surveillance videos. In: 2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), pp. 1–6 (2013)

    Google Scholar 

  16. Zin, T.T., Tin, P., Hama, H., Toriu, T.: An integrated framework for detecting suspicious behaviors in video surveillance. In: Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series (2014)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to F. Persia .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Persia, F., D’Auria, D., Sperlí, G., Tufano, A. (2015). A Prototype for Anomaly Detection in Video Surveillance Context. In: Fujita, H., Guizzi, G. (eds) Intelligent Software Methodologies, Tools and Techniques. SoMeT 2015. Communications in Computer and Information Science, vol 532. Springer, Cham. https://doi.org/10.1007/978-3-319-22689-7_40

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-22689-7_40

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-22688-0

  • Online ISBN: 978-3-319-22689-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics