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Vision-guided localization for automated camera control

In this paper we report on research we are carrying out on camera localization and control for remote viewing during teleoperation. We present an approach to the localization problem which exploits a model of the task environment to guide the selection of vision filters for picking out `interesting' features. This research adapts the `interest' operator ideas of Moravec within a model-based vision framework. We present initial results which demonstrate the utility of feature-sensitive interest operators for picking out key visual landmarks.