Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/9539
Title: iJADE surveillant - an intelligent multi-resolution composite neuro-oscillatory agent-based surveillance system
Authors: Lee, RST
Keywords: Surveillance system
Composite Neuro-Oscillatory Wavelet-based (CNOW) model
Elastic Graph Dynamic Link Model (EGDLM)MPEG-7
Neural networks
Issue Date: 2003
Publisher: Elsevier
Source: Pattern recognition, 2003, v. 36, no. 6, p. 1425-1444 How to cite?
Journal: Pattern recognition 
Abstract: Due to the rapid development of technology, especially in the field of Internet systems, there is an increasing demand both for intelligent, mobile and autonomous systems and for the usage and conveyance of multi-media information through cyberspace. In this paper, we propose an innovative, intelligent multi-agent based model, namely intelligent Java Agent Development Environment (iJADE), to provide an intelligent agent-based platform in the e-commerce environment. In addition to the facilities found in contemporary agent development platforms, which focus on the autonomy and mobility of multi-agents, iJADE provides an intelligent layer (known as the “Conscious Layer”) to support the implementation of various AI functionalities in order to produce “smart” agents.
From an implementation point of view, we introduce an intelligent, multi-media processing system known as “iJADE Surveillant”—an intelligent multi-resolution composite neuro-oscillatory agent-based surveillance system—which is based on the integration of the following modules. (a) An automatic coarse-to-fine figure-ground scene segmentation module using the Composite Neuro-Oscillatory Wavelet-based model. (b) An automatic human face detection and extraction module using an Active Contour Model with facial “landmarks” vectors. (c) Invariant human face identification based on the Elastic Graph Dynamic Link Model. To conform to the current (and future) multi-media system standards, all of iJADE Surveillant is implemented using the MPEG-7 system framework—with comprehensive Description Schemes, feature descriptors and a model framework.
From an experimental point of view, a scene gallery of over 6000 color scene images is used to test the automatic scene segmentation. One hundred distinct human subjects (with over 1020 tested scenes) are used to test the intelligent human face identification. An overall correct (invariant) facial recognition rate of over 90% is attained. We hope that the implementation of the iJADE Surveillant can provide an invariant and higher-order intelligent object (pattern) encoding, searching and identification solution for future MPEG-7 applications.
URI: http://hdl.handle.net/10397/9539
ISSN: 0031-3203
EISSN: 1873-5142
DOI: 10.1016/S0031-3203(02)00255-8
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