Accession Number:

ADA460919

Title:

Objective Functions for Feature Discrimination

Descriptive Note:

Technical note

Corporate Author:

SRI INTERNATIONAL MENLO PARK CA ARTIFICIAL INTELLIGENCE CENTER

Personal Author(s):

Report Date:

1989-05-01

Pagination or Media Count:

9.0

Abstract:

We propose and evaluate a class of objective functions that rank hypotheses for feature labels. Our approach takes into account the representation cost and quality of the shapes themselves, and balances the geometric requirements against the photometric evidence. This balance is essential for any system using Under constrained or generic feature models. We introduce examples of specific models allowing the actual computation of the terms in the objective function, and show how this framework leads naturally to control parameters that have a clear semantic meaning. We illustrate the properties of our objective functions on synthetic and real images.

Subject Categories:

  • Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE