Lilly Suriani Affendey

Work place: Faculty of Computer Science and Information Technology, University Putra Malaysia, Malaysia

E-mail: suriani@fsktm.upm.edu.my

Website:

Research Interests: Computer Architecture and Organization, Data Mining, Data Structures and Algorithms, Models of Computation

Biography

Lilly Suriani Affendey: received her Bachelor of Computer Science Degree from University of Agriculture, Malaysia in 1991 and M. Sc in Computing from the University of Bradford, UK in1994. In 2007 she received her Ph.D. from University Putra Malaysia. She is currently a senior lecturer in the Faculty of Computer Science and Information Technology, UPM and Head of the Department of computer science. Her research interest is in Multimedia Databases, Video Databases, Integration of Heterogeneous Databases, and Data Mining Application.

Author Articles
Systematic Review and Classification on Video Surveillance Systems

By Fereshteh Falah Chamasemani Lilly Suriani Affendey

DOI: https://doi.org/10.5815/ijitcs.2013.07.11, Pub. Date: 8 Jun. 2013

Recently, various conferences and journals have published articles related to Video Surveillance Systems, indicating researchers’ attention. The goal of this review is to examine the latest works were published in journals, propose a new classification framework of video surveillance systems and investigate each aspect of this classification framework. This paper provides a comprehensive and systematic literature review of video surveillance systems from 2010-2011, extracted from six online digital libraries using article’s title and keyword. The proposed classification framework is expanded on the basis of architecture of video surveillance systems, which is composed of six layers: Concept and Foundation Layer, Network Infrastructure Layer, Processing Layer, Communication Layer, Application Layer, and User Interaction Layer. This review shows, although many publication and research focus on real-time aspect of the challenge, only few researches have investigated the deployment of extracted and retrieved information for forensic video surveillance.

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