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Wide area surveillance: Situational awareness for security automa | 28369

Journal of Information Technology & Software Engineering

ISSN - 2165- 7866

+44 1300 500008

Wide area surveillance: Situational awareness for security automation

Global Summit and Expo on Multimedia & Applications

August 10-11, 2015 Birmingham, UK

Vijayan K Asari

Scientific Tracks Abstracts: J Inform Tech Soft Engg

Abstract :

Wide area surveillance refers to an automated monitoring process that involves data acquisition, analysis, and interpretation
for understanding object behaviors. Automated surveillance systems are mostly used for military, law enforcement, and
commercial applications. Sensors of different types and characteristics in surface-based or aerial-based platforms are used for
the acquisition of data of large areas sometimes covering several square miles. Intelligent visual surveillance is becoming more
popular in applications such as human identification, activity recognition, behavior analysis, anomaly detection, alarming, etc.
Detection, tracking, and identification of moving objects in a wide area surveillance environment have been an active research
area in the past few decades. Object motion analysis and interpretation are integral components for activity monitoring and
situational awareness. Real-time performance of these data analysis tasks in a very wide field of view is an important need
for monitoring in security and law enforcement applications. Although huge strides have been made in the field of computer
vision related to technology development for automatic monitoring systems, there is a need for robust algorithms that can
perform detections of individuals in a surveillance environment. This is mainly because of certain constraints such as partial
occlusions of the body, heavily crowded scenes where people are very close to each other, etc. We present a robust automated
system which can detect and identify people by automated face recognition in a surveillance environment and track their
actions and activities by a spatio-temporal feature tracking mechanism.

Biography :

Vijayan K Asari is a Professor in Electrical and Computer Engineering and an Endowed Chair in Wide Area Surveillance at the University of Dayton, USA. He is
the Director of the Center of Excellence for Computer Vision and Wide Area Surveillance Research at UD. He received his PhD degree in Electrical Engineering
from the Indian Institute of Technology, Madras. He holds three patents and has published more than 450 research papers in the areas of image processing and
computer vision. He received several teaching, research and advising awards. He is a Senior Member of IEEE and SPIE.

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