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  Center-surround patterns emerge as optimal predictors for human saccade targets

Kienzle, W., Franz, M., Schölkopf, B., & Wichmann, F. (2009). Center-surround patterns emerge as optimal predictors for human saccade targets. Journal of Vision, 9(5): 7, pp. 1-15. doi:10.1167/9.5.7.

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Kienzle, W1, 2, Autor           
Franz, MO1, 2, Autor           
Schölkopf, B1, 2, Autor           
Wichmann, FA1, 2, Autor           
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Zusammenfassung: The human visual system is foveated, that is, outside the central visual field resolution and acuity drop rapidly. Nonetheless much of a visual scene is perceived after only a few saccadic eye movements, suggesting an effective strategy for selecting saccade targets. It has been known for some time that local image structure at saccade targets influences the selection process. However, the question of what the most relevant visual features are is still under debate. Here we show that center-surround patterns emerge as the optimal solution for predicting saccade targets from their local image structure. The resulting model, a one-layer feed-forward network, is surprisingly simple compared to previously suggested models which assume much more complex computations such as multi-scale processing and multiple feature channels. Nevertheless, our model is equally predictive. Furthermore, our findings are consistent with neurophysiological hardware in the superior colliculus. Bottom-up visual saliency may thus not be computed cortically as has been thought previously.

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 Datum: 2009-05
 Publikationsstatus: Erschienen
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 Ort, Verlag, Ausgabe: -
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 Identifikatoren: DOI: 10.1167/9.5.7
BibTex Citekey: 5890
 Art des Abschluß: -

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Titel: Journal of Vision
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: Charlottesville, VA : Scholar One, Inc.
Seiten: - Band / Heft: 9 (5) Artikelnummer: 7 Start- / Endseite: 1 - 15 Identifikator: ISSN: 1534-7362
CoNE: https://pure.mpg.de/cone/journals/resource/111061245811050