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We present a novel visual attention tracking technique based on SharedAttention modeling. Our proposed method models the viewer as a participant inthe activity occurring in the scene. We go beyond image salience and instead ofonly computing the power of an image region to pull attention to it, we alsoconsider the strength with which other regions of the image push attention tothe region in question. We use the term Attentional Push to refer to the powerof image regions to direct and manipulate the attention allocation of theviewer. An attention model is presented that incorporates the Attentional Pushcues with standard image salience-based attention modeling algorithms toimprove the ability to predict where viewers will fixate. Experimentalevaluation validates significant improvements in predicting viewers' fixationsusing the proposed methodology in both static and dynamic imagery.

Attentional Push: Augmenting Salience with Shared Attention Modeling