Classifying other agents’ intentions is a very complex task but it can be very essential in assisting (autonomous or human) agents in navigating safely in dynamic and possibly hostile environments. This paper introduces a classification approach based on support vector machines and Bayesian filtering (SVM-BF). It then applies it to a road intersection problem to assist a vehicle in detecting the intention of an approaching suspicious vehicle. The SVM-BF approach achieved very promising results.
Using Support Vector Machines and Bayesian Filtering for Classifying Agent Intentions at Road Intersections
2009
Report
Electronic Resource
English
Classifying Acoustic Emission Data in Structural Health Monitoring using Support Vector Machines
British Library Conference Proceedings | 2010
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