On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence
Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence
ICIAP '97 Proceedings of the 9th International Conference on Image Analysis and Processing-Volume II
Aggregation operators for selection problems
Fuzzy Sets and Systems - Special issue: Soft decision analysis
Multi-Camera Multi-Person Tracking for EasyLiving
VS '00 Proceedings of the Third IEEE International Workshop on Visual Surveillance (VS'2000)
Using a multi-criteria decision making approach to evaluate mobile phone alternatives
Computer Standards & Interfaces
Information fusion for wireless sensor networks: Methods, models, and classifications
ACM Computing Surveys (CSUR)
Mobile-agent-based collaborative sensor fusion
Information Fusion
Monitoring Complex Environments Using a Knowledge-Driven Approach Based on Intelligent Agents
IEEE Intelligent Systems
PRISMATICA: toward ambient intelligence in public transport environments
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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Intelligent surveillance systems should be able to carry out an exhaustive analysis from multi-sensor information according to multiple events of interest in order to classify situations as normal or abnormal. That is why the design of appropriate fusion methods is essential to combine the information from a number of monitored aspects and achieve a reliable interpretation of the environment state. Unfortunately, these systems operate under highly dynamic conditions. A static configuration of the weights that determine the importance of the monitored aspects or events of interest may lead to a high number of false alarms and the ignorance of critical situations. This paper performs a thorough study of different information fusion algorithms and proposes a method for the automatic reweighting of the values that establish the importance of the analyzed events of interest. This online method is flexible enough for adjusting such weights in each monitored situation to address the dynamic nature of real environments. The experiments, which have been conducted in a real urban traffic environment, demonstrate the feasibility of the proposed method.