On the Automated Construction of Image-Based Maps
Tóm tắt
For many tasks, we wish to record or recover the description of a remote environment so that it can be inspected by a person. This is the problem we address in this paper. Rather than recovering a geometric description of an environment, as many robotics systems attempt to do, we seek to recover a model of an environment in terms of its appearance from a set of carefully selected viewpoints. Our hope is that this type of model is both more accessible to humans for many realistic tasks, and also more readily achieved with automated systems. These viewpoints are locations in the environment associated with views containing maximal visual interest. This approach to environment representation is analogous to image compression. Our goal is to obtain a set of representative views resembling those that would be selected by a human observer given the same task. Our computational procedure is inspired by models of human visual attention appearing 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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