Shape Des+cription with a Space-Variant Sensor: Algorithms for Scan-Path, Fusion, and Convergence Over Multiple Scans

One of the ways by which early human vision is sharply distinguished from machine vision is the fact that the human visual representation is strongly space-variant and the human system builds up a representation of a scene through multiple fixations during scanning. In this paper, we discuss three algorithms related to the “blending” of a single scene from multiple frames acquired from a space-variant sensor. 1) Given a series of space-variant contour-based scenes with different “fixation points,” we show how to fuse these into a single, multiscan view, which incorporates the information present in the individual scans. 2) We demonstrate an (attentional) algorithm which recursively examines the current knowledge of the scene in order to best choose the next fixation point, based on focusing attention in regions of maximum boundary curvature.