A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Attention is a mechanism present in most of the more complex and developed living beings. It is responsible for much of their ability to operate in real time in unstructured and dynamic environments with a limited amount of processing resources. In this paper, an architecture for developing attentional functions in agents is presented. This architecture is based on the concept of attentor and it allows for the real time adaptation to the environment and tasks to be performed in a natural manner. One of the main requirements of the system was the ability to handle different sensorial varieties and attentional streams in a transparent manner while, at the same time, being able to progressively create more complex attentional structures. The main characteristics of the architecture are presented through its implementation in a real robot.