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  A Nonparametric Approach to Bottom-Up Visual Saliency

Kienzle, W., Wichmann, F., Schölkopf, B., & Franz, M. (2007). A Nonparametric Approach to Bottom-Up Visual Saliency. Advances in Neural Information Processing Systems 19: Proceedings of the 2006 Conference, 689-696.

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 Urheber:
Kienzle, W1, 2, Autor           
Wichmann, FA1, 2, Autor           
Schölkopf, B1, 2, Autor           
Franz, MO1, 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: This paper addresses the bottom-up influence of local image
information on human eye movements. Most existing computational models use a set of biologically plausible linear filters, e.g., Gabor or Difference-of-Gaussians filters as a front-end, the outputs of which are nonlinearly combined into a real number that indicates visual saliency. Unfortunately, this requires many design parameters such as the number, type, and size of the
front-end filters, as well as the choice of nonlinearities,
weighting and normalization schemes etc., for which biological plausibility cannot always be justified. As a result, these parameters have to be chosen in a more or less ad hoc way. Here, we propose to emphlearn a visual saliency model directly from human eye movement data. The model is rather simplistic and essentially parameter-free, and therefore contrasts recent developments in the field that usually aim at higher prediction rates at the cost of additional parameters and increasing model complexity. Experimental results show that - despite the lack of
any biological prior knowledge - our model performs comparably to existing approaches, and in fact learns image features that resemble findings from several previous studies. In particular, its maximally excitatory stimuli have center-surround structure, similar to receptive fields in the early human visual system.

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 Datum: 2007-09
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: BibTex Citekey: 4147
 Art des Abschluß: -

Veranstaltung

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Titel: Twentieth Annual Conference on Neural Information Processing Systems (NIPS 2006)
Veranstaltungsort: Vancouver, BC, Canada
Start-/Enddatum: 2006-12-04 - 2006-12-07

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Titel: Advances in Neural Information Processing Systems 19: Proceedings of the 2006 Conference
Genre der Quelle: Zeitschrift
 Urheber:
Schölkopf, B1, Herausgeber           
Platt, JC, Herausgeber
Hoffman, T, Herausgeber
Affiliations:
1 Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795            
Ort, Verlag, Ausgabe: Cambridge, MA, USA : MIT Press
Seiten: - Band / Heft: - Artikelnummer: - Start- / Endseite: 689 - 696 Identifikator: ISBN: 0-262-19568-2