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A Computational Perspective on Visual Attention$
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John K. Tsotsos

Print publication date: 2011

Print ISBN-13: 9780262015417

Published to MIT Press Scholarship Online: August 2013

DOI: 10.7551/mitpress/9780262015417.001.0001

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Selective Tuning: Overview

Selective Tuning: Overview

Chapter:
(p.80) (p.81) 4 Selective Tuning: Overview
Source:
A Computational Perspective on Visual Attention
Author(s):

John K. Tsotsos

Publisher:
The MIT Press
DOI:10.7551/mitpress/9780262015417.003.0004

This chapter provides an overview of the Selective Tuning (ST) model of visual attention. The visual processing structure is composed of different parts where layers of neurons are present with decreasing spatial resolution and increasing complexity of selectivity in upper layers. Each neuron has branching connections with the next highest layer and receives coinciding information from neurons in the lower layer. The selection technique of ST depends on a layered process where different layers play a key role in selecting the component required for visual attention. The ST algorithm also plays a key role in selecting different sensory components required for visual attention. The algorithm can be used effectively for visual attention under task-based and free-viewing conditions.

Keywords:   ST, neurons, branching connections, selection technique, components

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