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  Learning Eye Movements

Kienzle, W., Wichmann, F., Schölkopf, B., & Franz, M. (2006). Learning Eye Movements. Poster presented at Gordon Research Conference: Sensory Coding & the Natural Environment, Big Sky, MT, USA.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-D06B-9 Version Permalink: http://hdl.handle.net/21.11116/0000-0004-B596-6
Genre: Poster

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 Creators:
Kienzle, W1, 2, Author              
Wichmann, FA1, 2, Author              
Schölkopf, B1, 2, Author              
Franz, MO1, 2, Author              
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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 Abstract: The human visual system samples images through saccadic eye movements which rapidly change the point of fixation. Although the selection of eye movement targets depends on numerous top-down mechanisms, a number of recent studies have shown that low-level image features such as local contrast or edges play an important role. These studies typically used predefined image features which were afterwards experimentally verified. Here, we follow a complementary approach: instead of testing a set of candidate image features, we infer these hypotheses from the data, using methods from statistical learning. To this end, we train a non-linear classifier on fixated vs. randomly selected image patches without making any physiological assumptions. The resulting classifier can be essentially characterized by a nonlinear combination of two center-surround receptive fields. We find that the prediction performance of this simple model on our eye movement data is indistinguishable from the physiologically motivated model of Itti amp; Koch (2000) which is far more complex. In particular, we obtain a comparable performance without using any multi-scale representations, long-range interactions or oriented image features.

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 Dates: 2006-09
 Publication Status: Published online
 Pages: -
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 Rev. Method: -
 Identifiers: BibTex Citekey: 4154
 Degree: -

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Title: Gordon Research Conference: Sensory Coding & the Natural Environment
Place of Event: Big Sky, MT, USA
Start-/End Date: 2006-08-27 - 2006-09-01

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