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Cited by 3,439

The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.

Graph-Based Visual Saliency

Harel, Jonathan, Koch, Christof, Perona, Pietro·2007·Advances in Neural Information Processing Systems 19

Abstract

A new bottom-up visual saliency model, Graph-Based Visual Saliency (GBVS), is proposed. It consists of two steps: first forming activation maps on certain feature \nchannels, and then normalizing them in a way which highlights conspicuity and admits combination with other maps. The model is simple, and biologically plausible \ninsofar as it is naturally parallelized. This model powerfully predicts human fixations on 749 variations of 108 natural images, achieving 98% of the ROC area \nof a human-based control, whereas the classical algorithms of Itti & Koch ([2], [3], [4]) achieve only 84%.

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Crossref · 10.7551/mitpress/7503.003.0073

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Metadata

Authors
Harel, J., Koch, C., & Perona, P.
Venue
Advances in Neural Information Processing Systems 19
Publisher
The MIT Press
Published
2007-09-07
Pages
545-552
OpenAlex
W2135957164
Cited by
3,439
References
12
FWCI
49.53
Type
book chapter
Language
en
Open access
closed

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