From Saliency to Eye Gaze: Embodied Visual Selection for a Pan-Tilt-Based Robotic Head
This paper introduces a model of gaze behavior suitable for robotic active vision. Built upon a saliency map taking into account motion saliency, the presented model estimates the dynamics of different eye movements, allowing to switch from fixational movements, to saccades and to smooth pursuit. We investigate the effect of the embodiment of attentive visual selection in a pan-tilt camera system. The constrained physical system is unable to follow the important fluctuations characterizing the maxima of a saliency map and a strategy is required to dynamically select what is worth attending and the behavior, fixation or target pursuing, to adopt. The main contributions of this work are a novel approach toward real time, motion-based saliency computation in video sequences, a dynamic model for gaze prediction from the saliency map, and the embodiment of the modeled dynamics to control active visual sensing.
KeywordsGround Truth Local Maximum Smooth Pursuit Active Vision Transition Kernel
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