One of the first steps of any visual system is that of locating suitable interest points, "salient regions", in the scene, to detect events, and eventually to direct gaze toward these locations. In the last few years, object-based visual attention models have received an increasing interest in the literature, the problem, in this case, being that of creating a model of "objecthood" that eventually guides a saliency mechanism. We propose here an object-based model of visual attention and show its instantiation on a humanoid robot. The robot employs action to learn and define its own concept of objecthood.
Object-based Visual Attention: a Model for a Behaving Robot
2005-01-01
707896 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
A visual attention model for robot object tracking
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