Image classifier and scene understanding systems of multiagent teams
John Mashford, W. Dai, Robin Drogemuller, B. Marksjo · 2002
A multi-agent architecture for scene understanding systems is described. Such systems consist of a collection of coupled vision subsystems, each one dedicated to a particular sensor. Interaction between the vision subsystems is controlled by an organising agent. Each vision subsystem is implemented on the basis of a partition tree image labelling representation and an associated multi-agent hierarchy of classifiers controlled by an organising agent. Each classifier in the multi-agent hierarchy of classifiers may be implemented as a decision tree of neural network classifiers acting on feature vectors derived from regions in the partition tree. Therefore, the image labelling and image classification subsystems can be described in terms of hierarchical networks of neural networks from which an interpretation in terms of multi-agents follows very naturally. The vision subsystems have a multi-resolution image representation and concurrency between and within the image labelling and image classification vision subsystem components.