Operating systems (3rd ed.): internals and design principles
Operating systems (3rd ed.): internals and design principles
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion Understanding: Task-Directed Attention and Representations that Link Perception with Action
International Journal of Computer Vision
A Context-Dependent Attention System for a Social Robot
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Neural Networks - 2006 Special issue: The brain mechanisms of imitation learning
Autonomous switching of top-down and bottom-up attention selection for vision guided mobile robots
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Autonomous behavior-based switched top-down and bottom-up visual attention for mobile robots
IEEE Transactions on Robotics
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The limited visual and computational resources available during the perception of a human action makes a visual attention mechanism essential. In this paper we propose an attention mechanism that combines the saliency of top-down (or goal-directed) elements, based on multiple hypotheses about the demonstrated action, with the saliency of bottom-up (or stimulus-driven) components. Furthermore, we use the bottom-up part to initialise the top-down, hence resulting in a selection of the behaviours that rightly require the limited computational resources. This attention mechanism is then combined with an action understanding model and implemented on a robot, where we examine its performance during the observation of object-directed human actions.