Shape Description with a Space Variant Sensor: Algorithms for Scan-Path, Fusion and Convergence Over Multiple Scans
Abstract
One of the ways by which early human vision is sharply distinguished from machine vision is by the fact that the human visual representation is strongly space variant and that 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, multi-scan 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. 3) We discuss a simple metric for evaluating 'convergence' over scan-path. This may be used to quantify the performance of (2) above, i.e. to compare the performance of various 'attentional' algorithms. Finally, we discuss this work in the light of both machine and biological vision.
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 01, 1987
- Accession Number
- ADA209984
Entities
People
- Eric L. Schwartz
- Yehezkel Yeshurun
Organizations
- New York University