Appiah, Kofi, Hunter, Andrew, Owens, Jonathan , Aiken, Phil and Lewis, Katrina (2009) Autonomous real-time surveillance system with distributed IP cameras. In: Third ACM/IEEE International Conference on Distributed Smart Cameras, 30 August - 2 September, 2009, Como, Italy.
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| Item Type: | Conference or Workshop contribution (Paper) |
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| Item Status: | Live Archive |
Abstract
An autonomous Internet Protocol (IP) camera based object tracking and behaviour identification system, capable of running in real-time on an embedded system with limited memory and processing power is presented in this paper. The main contribution of this work is the integration of processor intensive image processing algorithms on an embedded platform capable of running at real-time for monitoring the behaviour of pedestrians. The Algorithm Based Object Recognition and Tracking (ABORAT) system architecture presented here was developed on an Intel PXA270-based development board clocked at 520 MHz. The platform was connected to a commercial stationary IP-based camera in a remote monitoring station for intelligent image
processing. The system is capable of detecting moving objects and their shadows in a complex environment with varying lighting intensity and moving foliage. Objects
moving close to each other are also detected to extract their trajectories which are then fed into an unsupervised neural network for autonomous classification. The novel intelligent video system presented is also capable of performing simple analytic functions such as tracking and generating alerts when objects enter/leave regions or cross tripwires superimposed on live video by the operator.
| Additional Information: | An autonomous Internet Protocol (IP) camera based object tracking and behaviour identification system, capable of running in real-time on an embedded system with limited memory and processing power is presented in this paper. The main contribution of this work is the integration of processor intensive image processing algorithms on an embedded platform capable of running at real-time for monitoring the behaviour of pedestrians. The Algorithm Based Object Recognition and Tracking (ABORAT) system architecture presented here was developed on an Intel PXA270-based development board clocked at 520 MHz. The platform was connected to a commercial stationary IP-based camera in a remote monitoring station for intelligent image processing. The system is capable of detecting moving objects and their shadows in a complex environment with varying lighting intensity and moving foliage. Objects moving close to each other are also detected to extract their trajectories which are then fed into an unsupervised neural network for autonomous classification. The novel intelligent video system presented is also capable of performing simple analytic functions such as tracking and generating alerts when objects enter/leave regions or cross tripwires superimposed on live video by the operator. |
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| Keywords: | Algorithm Based Object Recognition and Tracking, IP cameras, security surveillance |
| Subjects: | G Mathematical and Computer Sciences > G700 Artificial Intelligence G Mathematical and Computer Sciences > G400 Computer Science |
| Divisions: | College of Science > School of Computer Science |
| ID Code: | 2008 |
| Deposited On: | 21 Sep 2009 09:28 |
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