Heiko Schütt: New abstract accepted as a poster at ECVP from 27.08.-31.08.2017 in Berlin
Title: "Using an Image-Computable Early Vision Model to Predict Eye Movements" by Heiko H. Schütt, Lars O. M. Rothkegel, Hans A. Trukenbrod, Ralf Engbert & Felix A. Wichmann
It is widely believed that early visual processing influences eye movements via bottom-up visual saliency calculations. However, direct tests of this hypothesis in natural scenes have been rare as image-computable models of early visual processing were lacking. We recently developed an image-computable early vision model, and thus we now have the means to investigate the connection from early vision to eye movements.
Here we explore eye movement data measured while subjects searched for simple early vision inspired targets like Gabors and Gaussian blobs overlaid over natural scenes. We compare the output of the early vision model processing patches around fixated locations with randomly chosen patches. Additionally we use a neural network to predict the fixation density from the early vision model output. Finally we use the model's predictions of target detectability to predict search performance.
We find clear differences between the early vision outputs at fixated locations which roughly follow the activations generated by the target alone. Additionally the fixation density can be predicted reasonably well from the early vision outputs using different weightings for different targets. Finally, target detectability at the specific location predicts search performance in terms of both the probability of finding the target and the time needed to find them.
Our findings show a clear dependence between eye movements and early visual processing. Additionally they highlight the possibility to use our spatial vision model as a preprocessing step for models of mid- and high-level vision.
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