Abstract
Eye movements contain information that can be used to recognize actions in still images and enhance automatic computer vision methods. Information in Eye Movements • Different action classes elicit different spatio-temporal gaze patterns from viewers. • Gaze features are derived and used to train Support Vector Machine (SVM) classifiers. • Confusion in the gaze classifier reveals behaviorally-meaningful action groups. Information in Pixels • Convolutional Neural Network (CNN) features are computed for an image and are used to train SVM classifiers for each action. Goal •Explore relationship between gaze patterns and pixels describing actions in images. •Show usefulness of gaze, alone or combined with computer vision, to classify images.
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