Object detection and recognition is a topic of significant
interest in computer and robot vision. It is required in most
applications of computational vision, for example, biometric
systems, medical imaging, intelligent cars, factory automation, and
image databases.
One of the major challenges in designing object recognition
systems is to construct methods that are fast and capable of
operating on standard computer platforms. The more developed such
systems become, the more urgent becomes the need for a
pre-selection system that enables subsequent processing to focus
only on relevant data. One mechanism to achieve this is visual
attention: it selects regions in a visual scene that are most
likely to contain objects of interest. The field of visual
attention is currently the focus of much research for both
biological and artificial systems.
This monograph presents a complete computational system for
visual attention and object detection: VOCUS (Visual Object
detection with a CompUtational attention System) is a system
capable of automatically selecting regions of interest in images
and detecting specific objects. It represents a major step forward
on integrating data-driven and model-driven information into a
single framework. Additionally, the volume contains an extensive
review of the literature on visual attention, detailed evaluations
of VOCUS in different settings, and applications of the system in
the context of object recognition and robotics.
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