On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision: A Modern Approach
Computer Vision: A Modern Approach
A New Approach to Object-Oriented Middleware
IEEE Internet Computing
Multi-agent framework in visual sensor networks
EURASIP Journal on Applied Signal Processing
General Tensor Discriminant Analysis and Gabor Features for Gait Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Vision and Applications
A cognitive surveillance system for detecting incorrect traffic behaviors
Expert Systems with Applications: An International Journal
Scenario-based query processing for video-surveillance archives
Engineering Applications of Artificial Intelligence
PRISMATICA: toward ambient intelligence in public transport environments
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Real-time video-shot detection for scene surveillance applications
IEEE Transactions on Image Processing
Human Gait Recognition With Matrix Representation
IEEE Transactions on Circuits and Systems for Video Technology
A hierarchical self-organizing approach for learning the patterns of motion trajectories
IEEE Transactions on Neural Networks
Expert Systems with Applications: An International Journal
Genetic programming based blind image deconvolution for surveillancesystems
Engineering Applications of Artificial Intelligence
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Intelligent surveillance involves the use of AI techniques to monitor environments whose analysis is becoming more and more complex because of the large number of sensors used and the need of monitoring multiple events of interest simultaneously. Most of the current surveillance systems provide solutions for particular problems but still suffer from lack of flexibility and scalability when they are used on different or related surveillance problems. To overcome this limitation, two aspects should be addressed: a knowledge-based surveillance model flexible enough to deal with different events of interest and an architecture that gives support to this model when deploying the surveillance system within a particular scenario. This paper discusses the architecture devised to deploy intelligent surveillance systems by means of a set of autonomous agents that are responsible for the management of different surveillance tasks and for cooperating to monitor complex environments. This multi-agent architecture is inspired by a normality-based formal model used to define the knowledge needed to analyze general-purpose surveillance concepts. We use the architecture to deploy a surveillance system to monitor an urban traffic scenario.