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

Authors:
Claudio M. Privitera;Lawrence W. Stark
Affiliations:
Univ. of California, Berkeley;Univ. of California, Berkeley
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
2000

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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.