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

Authors:
Y. Yeshurun;E. L. Schwartz
Affiliations:
Tel Aviv Univ., Tel Aviv, Isreal;New York Univ., New York, NY
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
1989

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Abstract

The authors discuss three algorithms related to the blending of a single scene from multiple frames acquired from a space-variant sensor. Given a series of space-variant contour-based scenes with different fixation points, they show how to fuse these into a single multiscan view, which incorporates the information present in the individual scans. They demonstrate an (attentional) algorithm which recursively examines the current knowledge of the scene in order best to choose the next fixation point in terms of focusing attention on regions of maximum boundary curvature. They discuss a simple metric for evaluating convergence over a scan path. This may be used to compare the performance of various attentional algorithms. They discuss their work in light of both machine and biological vision.