Panoramic attention for humanoid robots

In this paper, we present a novel three-layer model of panoramic attention for our humanoid robot. In contrast to similar architectures employing coarse discretizations of the panoramic field, saliencies are maintained only for cognitively prominent entities(e.g. faces). In the absence of attention triggers, an idle-policy makes the humanoid span the visual field of panorama imparting a human-like idle gaze while simultaneously registering attention-worthy entities. We also describe a model of cognitive panoramic habituation which maintains entity-specific persistence models, thus imparting lifetimes to entities registered across the panorama. This mechanism enables the memories of entities in the panorama to fade away, creating a human-like attentional effect. We describe scenarios demonstrating the aforementioned aspects. In addition, we present experimental results which demonstrate how the cognitive filtering aspect of our model reduces processing time and false-positive rates for standard entity related modules such as face-detection and recognition.