Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Abandoned Bag Detection in Video Surveillance Using Image Processing

Author : Nalini Jajula 1 Y Jaya Lakshmi 2

Date of Publication :23rd August 2019

Abstract: A key technology to fight against terrorism and crime for public safety, moving object detection and tracking has become very popular and one of the challenging research topic in various security areas of computer vision and video surveillance applications. Generally, an object is said to be abandoned if it is kept at a particular space in a video surveillance system & unattended for long time. An automatic abandoned object detection system typically uses a combination of background subtraction and object tracking to look for certain predefined patterns of activity that occur when an object is left behind by its owner. We propose a method to detect abandoned object from surveillance video using Image Processing. In first step, foreground objects are extracted using background subtraction methods. In second step, static objects are detected by using contour features of foreground objects of consecutive frames. In third step, detected static objects are classified into human and non-human objects by using edge based object recognition method. Nonhuman static object is analyzed to detect abandoned object. Experimental results show that proposed system is efficient and effective for real-time video surveillance.

Reference :

    1. Dedeoglu, Y., Toreyin, B.U., Gudukbay, U., Cetin, A.E. (2006). Silhouette-Based Method for Object Classification and Human Action Recognition in Video, SpringerVerlag Berlin Heidelberg, 2006.
    2. Guler, S., & Farrow, M.K. (2006). Abandoned Object Detection in Crowded Places. Proceeding 9th IEEE International Workshop on PETS, 99-106, 2006
    3. Hazlewood, P. (2006, November 2). Britain becoming a ‘surveillance society’, Retrieved June 11, 2007, from http://www.ioltechnology.co.za/article_page.php?iSe ctionId=2885&iArticleId=35179 41
    4. Kim, K., Chalidabhongse, T.H., Harwood, D., & Davis, L. (2005). Background Modelling and Subtraction by Codebook Construction, Computer Vision Lab, University of Maryland, 2005.
    5. Kim, K., Chalidabhongse, T.H., Harwood, D., & Davis, L. (2005). Real-time foreground-background segmentation using codebook model, Elsevier Ltd, 2005.
    6. Kim, K., Harwood, D., Davis, L.S., (2005). Background Updating for Visual Surveillance, Springer-Verlag Berlin Heidelberg, 2005.
    7. Kirkup, M., & Carrigan M. (n.d.). Video surveillance research in retailing: ethical issues, Retrieved June 11, 2007, from http://www.emeraldinsight.com/Insight/ViewContent Servlet?Filename=Published/E meraldFullTextArticle/Articles/0890281103.html
    8. Li, L., Luo, R., Huang, W., & Eng, H. (2006). ContextControlled Adaptive Background Subtraction. Proceeding 9th IEEE International Workshop on PETS, 3138, 2006.
    9. Lv, F., Song, X., Wu, B., Singh, V.K., & Nevatia, R. (2006). Left-Luggage Detection using Bayesian Inference. Proceeding 9th IEEE International Workshop on PETS, 8390, 2006.
    10. Manning. S. (2007, February 26). Cameras taught to watch and learn, Retrieved June 11, 2007, from http://www.ioltechnology.co.za/article_page.php?iSe ctionId=2885&iArticleId=3702 503
    11. Peer, P., Kovac, J., Solina, F. 2003. Human skin colour clustering for face detection. In submitted to EUROCON 2003 – International Conference on Computer as a Tool.
    12. Smith, K., Quelhas, P., & Gatica-Perez, D. (2006). Detecting Abandoned Luggage Items in a Public Space. Proceeding 9th IEEE International Workshop on PETS, 7582, 2006.
    13. Thirde, D., Li, L., & Ferryman, J (2006). Overview of the PETS2006 Challenge. Proceeding 9th IEEE International Workshop on PETS, 47-50, 2006.
    14. Y. N. Wu, Z. Si, H. Gong, and S. C. Zhu, "Learning Active Basis Model for Object Detection and Recognition," International Journal of Computer Vision, pp. 1-38, 2009.
    15. X. Ren, C. C. Fowlkes, and J. Malik, "Learning probabilistic models for contour completion in natural images," International Journal of Computer Vision, vol. 77, pp. 47-63, 2008
    16. A. Y. S. Chia, S. Rahardja, D. Rajan, and M. K. H. Leung, "Structural descriptors for category level object detection," IEEE Transactions on Multimedia, vol. 11, pp. 1407-1421, 2009.
    17. J. Winn and J. Shotton, "The layout consistent random field for recognizing and segmenting partially occluded objects," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2006, pp. 37-44.
    18. V. Ferrari, T. Tuytelaars, and L. Van Gool, "Object detection by contour segment networks," in Lecture Notes in Computer Science vol. 3953, ed, 2006, pp. 14-28.
    19. K. Mikolajczyk, B. Leibe, and B. Schiele, "Multiple object class detection with a generative model," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2006, pp. 26-33.
    20. R. C. Nelson and A. Selinger, "Cubist approach to object recognition," in Proceedings of the IEEE International Conference on Computer Vision, 1998, pp. 614-621.
    21. V. Ferrari, L. Fevrier, F. Jurie, and C. Schmid, "Groups of adjacent contour segments for object detection," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, pp. 36-51, 2008.
    22. S. Ali and M. Shah, "A supervised learning framework for generic object detection in images," in Proceedings of the IEEE International Conference on Computer Vision, 2005, pp. 1347-1354.
    23. P. F. Felzenszwalb, "Learning models for object recognition," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2001, pp. 1056-1062.
    24. E. Borenstein and S. Ullman, "Learning to segment," in Lecture Notes in Computer Science vol. 3023, ed, 2004, pp. 315-328.
    25. E. Borenstein and J. Malik, "Shape guided object segmentation," in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2006, pp. 969-976.
    26. J. Wang, V. Athitsos, S. Sclaroff, and M. Betke, "Detecting objects of variable shape structure with Hidden State Shape Models," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, pp. 477-492, 2008.

Recent Article