Active detection and classification of junctions by foveation with a head-eye system guided by the scale-space primal sketch

Abstract

We consider how junction detection and classification can be performed in an active visual system. This is to exemplify that feature detection and classification in general can be done by both simple and robust methods, if the vision system is allowed to look at the world rather than at prerecorded images. We address issues on how to attract the attention to salient local image structures, as well as on how to characterize those.