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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