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Algorithms for Defining Visual Regions-of-Interest: Comparison with Eye Fixations

Published: 01 September 2000 Publication History

Abstract

Many machine vision applications, such as compression, pictorial database querying, and image understanding, often need to analyze in detail only a representative subset of the image, which may be arranged into sequences of loci called regions-of-interest, ROIs. We have investigated and developed a methodology that serves to automatically identify such a subset of aROIs (algorithmically detected ROIs) using different Image Processing Algorithms, IPAs, and appropriate clustering procedures. In human perception, an internal representation directs top-down, context-dependent sequences of eye movements to fixate on similar sequences of hROIs (human identified ROIs). In this paper, we introduce our methodology and we compare aROIs with hROIs as a criterion for evaluating and selecting bottom-up, context-free algorithms. An application is finally discussed.

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    Published In

    cover image IEEE Transactions on Pattern Analysis and Machine Intelligence
    IEEE Transactions on Pattern Analysis and Machine Intelligence  Volume 22, Issue 9
    September 2000
    142 pages
    ISSN:0162-8828
    Issue’s Table of Contents

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    IEEE Computer Society

    United States

    Publication History

    Published: 01 September 2000

    Author Tags

    1. Eye movements
    2. regions of interest identification and comparison.
    3. scanpath theory

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