Home   >   CSC-OpenAccess Library   >    Manuscript Information
Full Text Available

This is an Open Access publication published under CSC-OpenAccess Policy.
Publications from CSC-OpenAccess Library are being accessed from over 74 countries worldwide.
Event-Handling Based Smart Video Surveillance System
Md.Hazrat Ali, Fadhlan Hafiz, A.A Shafie, Othman Khalifa
Pages - 24 - 34     |    Revised - 25-03-2010     |    Published - 31-03-2010
Volume - 4   Issue - 1    |    Publication Date - March 2010  Table of Contents
Object detection, Visual surveillance, Object classification, Smart network
a broad range of applications. Moving object classification in the field of video surveillance is a key component of smart surveillance software. In this paper, we have proposed reliable software with its large features for people, vehicle and object classification which works well in challenging real-world constraints, including the presence of shadows, low resolution imagery, occlusion, perspective distortions, arbitrary camera viewpoints, and groups of people. We have discussed a generic model of smart video surveillance systems that can meet requirements of strong commercial applications and also shown the implication of the software for the security purposes which made the whole system as a smart network. Smart surveillance systems use automatic image understanding techniques to extract information from the surveillance data.
1 Google Scholar 
2 ScientificCommons 
3 CiteSeerX 
4 refSeek 
5 iSEEK 
6 Socol@r  
7 ResearchGATE 
8 Bielefeld Academic Search Engine (BASE) 
9 OpenJ-Gate 
10 Scribd 
11 SlideShare 
13 PdfSR 
1 W. Hu, T. Tab, L. Wang, and S. Maybank, “A Survey on Visual Surveillance of Object Motion and Behaviors,” IEEE Trans. Syst. Man Cybern?-- Part C: App. and Reviews, vol. 34, no. 3, pp. 334–352, 2004.
2 D. M. Gavrila, "The Visual Analysis of Human Movement: A survey," Computer Vision and Image Understanding, vol. 73, 1999, pp. 82-98.
3 C. S. Regazzoni, V. Ramesh, and G. L. Foresti, “Distributed Embedded Smart Cameras for Surveillance Applications”, Proceedings of the IEEE, 39(2), Oct 2006.
4 L. Brown, “View Independent Vehicle/Person Classification”, VSSN’04, October 15, 2004, New York, USA.
5 B. Bose and E. Grimson, “Improving object classification in far-field video”, CVPR, 2004.
6 Case Study by Seagate, "Smart Surveillance Systems Tap Reliability and Performance of Seagate SV35 Series Drives." CS509,October 2006.
7 L. Chen et al, “An Integrated System for Moving Object Classification in Surveillance Videos” IEEE Fifth International Conference on Advanced Video and Signal Based Surveillance.2008.
8 W. Wolf, B. Ozer, and T. Lv, “Smart Cameras as Embedded Systems”, IEEE Computer Science Journal , 35(9):48–53, Sep 2002.
9 Fadhlan Hafiz et.al, “Human Detection For Real-Time Video Surveillance”, In Proceedings of International Conference on Engineering Technology 2010, Kuala Lumpur, Malaysia, 2009
10 Tian, Y.l. Hampapur, “A Robust Salient Motion Detection with Complex Background for Real- Time Video Surveillance”, In: IEEE Computer Society Workshop on Motion and Video Computing, Breckenridge, Colorado, January 5 and 6, 2005
Mr. Md.Hazrat Ali
IIUM - Malaysia
Dr. Fadhlan Hafiz
- Malaysia
Dr. A.A Shafie
- Malaysia
Othman Khalifa
- Malaysia