Abstract
Humans involuntarily move their eyes when retrieving an
image from memory. This motion is often similar to actually
observing the image. We suggest to exploit this behavior as
a new modality in human computer interaction, using the
motion of the eyes as a descriptor of the image. Interaction
requires the user’s eyes to be tracked, but no voluntary physical activity.We perform a controlled ...
Abstract
Humans involuntarily move their eyes when retrieving an
image from memory. This motion is often similar to actually
observing the image. We suggest to exploit this behavior as
a new modality in human computer interaction, using the
motion of the eyes as a descriptor of the image. Interaction
requires the user’s eyes to be tracked, but no voluntary physical activity.We perform a controlled experiment and develop matching techniques using machine learning to investigate if images can be discriminated based on the gaze patterns recorded while users merely recall an image. Our results indicate that image retrieval is possible with an accuracy significantly above chance. We also show that these results generalize to images not used during training of the classifier and extends to uncontrolled settings in a realistic scenario.
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