This book presents state-of-the-art computational
attention models that have been successfully tested in diverse application
areas and can build the foundation for artificial systems to efficiently
explore, analyze, and understand natural scenes. It gives a comprehensive overview of the most recent
computational attention models for processing visual and acoustic input. It
covers the biological background of visual and auditory attention, as well as bottom-up and top-down attentional
mechanisms and discusses various applications. In the first part new approaches
for bottom-up visual and acoustic saliency models are presented and applied to
the task of audio-visual scene exploration of a robot. In the second part the
influence of top-down cues for attention modeling is investigated.
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