Modeling visual attention via selective tuning
Artificial Intelligence - Special volume on computer vision
Dynamic visual selective attention model
Neurocomputing
Stereo Saliency Map Considering Affective Factors in a Dynamic Environment
Neural Information Processing
Computational visual attention systems and their cognitive foundations: A survey
ACM Transactions on Applied Perception (TAP)
Implementation of visual attention system using bottom-up saliency map model
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Affective saliency map considering psychological distance
Neurocomputing
Implementation of face selective attention model on an embedded system
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part V
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A system using visual information to interact with its environment, e.g. a robot, needs to process an enormous amount of data. To ensure that the visual process has tractable complexity visual attention plays an important role.A visual process will always have a number of implicit and explicit tasks that defines its purpose. The present document discusses attention mechanisms for selection of visual input to respond to the current set of tasks. To provide a truly distributed approach to attention it is suggested to model the control using game theory, in particular coalition games.