NIGHT–TIME OUTDOOR SURVEILLANCE WITH MOBILE CAMERAS

Ferran Diego, Georgios Evangelidis, Joan Serrat

Abstract

This paper addresses the problem of video surveillance by mobile cameras. We present a method that allows online change detection in night–time outdoor surveillance. Because of the camera movement, background frames are not available and must be ”localized“ in former sequences and registered with the current frames. To this end, we propose a Frame Localization And Registration (FLAR) approach that solves the problem efficiently. Frames of former sequences define a database which is queried by current frames in turn. To quickly retrieve nearest neighbors, database is indexed through a visual dictionary method based on the SURF descriptor. Furthermore, the frame localization is benefited by a temporal filter that exploits the temporal coherence of videos. Next, the recently proposed ECC alignment scheme is used to spatially register the synchronized frames. Finally, change detection methods apply to aligned frames in order to mark suspicious areas. Experiments with real night sequences recorded by in-vehicle cameras demonstrate the performance of the proposed method and verify its efficiency and effectiveness against other methods.

References

  1. Bay, H., Ess, A., Tuytelaars, T., and Van Gool, L. (2008). Speeded-up robust features (surf). CVIU, 110(3):346- 359.
  2. Chakravarty, P., Zhang, A. M., Jarvis, R., and Kleeman, L. (2007). Anomaly detection and tracking for a patrolling robot. In Australasian Conf. on Robotics and Automation.
  3. Diego, F., Ponsa, D., Serrat, J., and Lopez, A. (2011). Video alignment for change detection. IEEE Trans. on Image Processing, 20(7):1858 -1869.
  4. Evangelidis, G. D. and Psarakis, E. Z. (2008). Parametric image alignment using enhanced correlation coefficient maximization. IEEE Trans. on PAMI, 30(10):1858-1865.
  5. Haberdar, H. (2010). Disparity map refinement for video based scene change detection using a mobile stereo camera platform. In Proc. of ICPR.
  6. Kong, H., Audibert, J.-Y., and Ponce, J. (2010). Detecting abandoned objects with a moving camera. IEEE Trans. on Image Processing, 19(8):2201 -2210.
  7. Lathi, P. (1998). Signal Processing and Linear Systems. Berkeley Cambridge Press.
  8. Liu, C., Yuen, J., Torralba, A., and Freeman, W. T. (2008). Sift flow: dense correspondence across different scenes. In Proc. of ECCV.
  9. Lowe, D. (2004). Distinctive image features from scale invariant keypoints. IJCV, 60(2):91-110.
  10. Marcenaro, L., Marchesotti, L., and Regazzoni, C. (2002). A multi-resolution outdoor dual camera system for robust video-event metadata extraction. In Proc. of the 5th Int. Conf. on Information Fusion, volume 2, pages 1184 - 1189.
  11. Primdahl, K., Katz, I., Feinstein, O., Mok, Y. L., Dahlkamp, H., Stavens, D., Montemerlo, M., and Thrun, S. (2005). Change detection from multiple camera images extended to non-stationary cameras. In Proc. of Field and Service Robotics.
  12. Radke, R. J., Andra, S., Al-Kofahi, O., and Roysam, B. (2005). Image change detection algorithms: A systematic survey. IEEE Trans. on Image Processing, 14:294-307.
  13. Sand, P. and Teller, S. (2004). Video matching. ACM Transactions on Graphics (Proc. SIGGRAPH), 22(3):592- 599.
  14. Serrat, J., Diego, F., Lumbreras, F., and Ì lvarez, J. (2007). Alignment of videos recorded from moving vehicles. In Proc. of 14th Int. Conf. on Image Analysis and Processing.
  15. Sivic, J. and Zisserman, A. (2009). Efficient visual search of videos cast as text retrieval. IEEE Trans. on PAMI, 31(4):591-606.
  16. Soibam, B., Shah, S. K., Chaudhry, A., and Eledath, J. (2009). Quantitative comparison of metrics for change detection for video patrolling. In ICCV Workshop on Video-Oriented Object and Event Classification.
  17. Szeliski, R. (2010). Computer Vision: Algorithms and Applications. Springer.
  18. Yang, G., Stewart, C., Sofka, M., and Tsai, C.-L. (2007). Registration of challenging image pairs: Initialization, estimation, and decision. IEEE Trans. on PAMI, 29(11):1973-1989.
Download


Paper Citation


in Harvard Style

Diego F., Evangelidis G. and Serrat J. (2012). NIGHT–TIME OUTDOOR SURVEILLANCE WITH MOBILE CAMERAS . In Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM, ISBN 978-989-8425-99-7, pages 365-371. DOI: 10.5220/0003758103650371


in Bibtex Style

@conference{icpram12,
author={Ferran Diego and Georgios Evangelidis and Joan Serrat},
title={NIGHT–TIME OUTDOOR SURVEILLANCE WITH MOBILE CAMERAS},
booktitle={Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,},
year={2012},
pages={365-371},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003758103650371},
isbn={978-989-8425-99-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,
TI - NIGHT–TIME OUTDOOR SURVEILLANCE WITH MOBILE CAMERAS
SN - 978-989-8425-99-7
AU - Diego F.
AU - Evangelidis G.
AU - Serrat J.
PY - 2012
SP - 365
EP - 371
DO - 10.5220/0003758103650371