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Exploring with a foveated robot eye system

Computer vision systems are becoming more and more anthropomorphic. In addition to taking an active vision approach, researchers are now investigating robot heads with biologically motivated space-variant sensors. We have designed such an exploring eye system for robot gaze control when observing an arbitrary scene. Our approach uses "retinal" images constructed from overlapping receptive fields that are mapped to form log-polar "cortical" images. We have implemented this system on a parallel SIMD machine using an efficient parallelization algorithm. In order to demonstrate our approach, we have formulated various types of attentional operators that are used to select interest points to drive the gaze control mechanism. We show that our system efficiently integrates images from space-variant snapshots in an arbitrary natural environment.