Security System and Surveillance Using Real Time Object Tracking and Multiple Cameras

Article Preview

Abstract:

In this paper we propose multiple cameras using real time tracking for surveillance and security system. It is extensively used in the research field of computer vision applications, like that video surveillance, authentication systems, robotics, pre-stage of MPEG4 image compression and user inter faces by gestures. The key components of tracking for surveillance system are extracting the feature, background subtraction and identification of extracted object. Video surveillance, object detection and tracking have drawn a successful increased interest in recent years. A object tracking can be understood as the problem of finding the path (i.e. trajectory) and it can be defined as a procedure to identify the different positions of the object in each frame of a video. Based on the previous work on single detection using single stationary camera, we extend the concept to enable the tracking of multiple object detection under multiple camera and also maintain a security based system by multiple camera to track person in indoor environment, to identify by my proposal system which consist of multiple camera to monitor a person. Present study mainly aims to provide security and detect the moving object in real time video sequences and live video streaming. Based on a robust algorithm for human body detection and tracking in videos created with support of multiple cameras.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 403-408)

Pages:

4968-4973

Citation:

Online since:

November 2011

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Yilmaz, A., Javed, O., and Shah, M. Object tracking: A survey, ACM Compute. Surv. 38, 4, Article 13 (Dec. 2006), 45 pages. DOI = 10. 1145/1177352. 1177355.

DOI: 10.1145/1177352.1177355

Google Scholar

[2] Morimoto, T. Kiriyama, O. Harada, Y. Adachi, H. Koide, Object Tracking in Video Pictures based on Image Segmentation and Pattern Matching, Circuits and Systems, 2005. ISCAS 2005. IEEE International Symposium on page(s): 3215- 3218 Vol. 4, (2005).

DOI: 10.1109/iscas.2005.1465312

Google Scholar

[3] Massimo Piccardi Background subtraction techniques: a review, Computer Vision Research Group (CVRG), University of Technology, Sydney (UTS), The ARC Centre of Excellence for Autonomous Systems (CAS) Faculty of Engineering, UTS, April 15, (2004).

Google Scholar

[4] Karan Gupta1, Anjali V. Kulkarni Implementation of an Automated Single Camera Object Tracking System Using Frame Differencing and Dynamic Template Matching, Springer Netherlands, 10. 1007/978-1-4020-8741-7, page(s): 245-250, Friday, August 15, (2008).

DOI: 10.1007/978-1-4020-8741-7_44

Google Scholar

[5] Toufiq Parag, Ahmed Elgammal, Anurag Mittal A Framework for Feature Selection for Background Subtraction, Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2, Pages: 1916 – 1923 : (2006).

DOI: 10.1109/cvpr.2006.24

Google Scholar

[6] Alan M. McIvor, Background Subtraction Techniques, Reveal Ltd, PO Box 128-221, Remuera, Auckland, NewZealand, alan. mcivor@reveal. co. nz.

Google Scholar

[7] Jiwei Yuan Zhongke Shi, A new segmentation method for image sequence of traffic scenes, Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress, Volume: 5, On page(s): 4049- 4053 Vol. 5, 15-19 June (2004).

DOI: 10.1109/wcica.2004.1342261

Google Scholar

[8] Chaohui Zhan, Xiaohui Duan, Shuoyu Xu, Zheng Song, Min Luo, An Improved Moving Object Detection Algorithm Based on Frame Difference and Edge Detection, Proceedings of the Fourth International Conference on Image and Graphics, IEEE Computer Society, Pages 519-523, (2007).

DOI: 10.1109/icig.2007.153

Google Scholar