On Focus-of-Attention by Active Focusing
Focus-of-attention is extremely important in human visual perception. If computer vision systems are to perform tasks in a complex, dynamic world they will have to be able to control processing in a way that is analogous to visual attention in humans.
In this paper we will investigate problems in connection with foveation, that is in examining selected regions of the world at high resolution. We will consider a static world viewed by an active observer that has this capability. The tasks we will consider is that of finding and classifying junctions of contours, features that give important information about 3-dimensional structure like object shape and occlusions. Since they are completely local features, we can study them without treating the problem of integrating local information into global cues. We will show that foveation, as simulated by controlled, active zooming, allows robust detection and classification of junctions with very simple algorithms.
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