| Summary: | This thesis presents an approach to the automated construction of visual maps, in the form of walk-throughs, of an unknown environment. Our approach is based on the selection of informative viewpoints within the environment. These viewpoints are locations in the environment which correspond to views containing maximal visual interest. This approach to environment representation is analogous to image compression. Our goal is to obtain a set of selections resembling those made by a human observer given the same task. === Our computational procedure is inspired by models of human visual attention outlined in the literature on human psychophysics. We make use of the underlying edge structure of a scene, as it is largely unaffected by variations in illumination. Our implementation uses a mobile robot to traverse the environment, and then builds an image-based virtual representation of the environment, only keeping the views whose responses were highest. We demonstrate the effectiveness of our attention operator on both single images, and in viewpoint selection within an unknown environment.
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