Accession Number:

ADA190384

Title:

Energy Functions for Early Vision and Analog Networks.

Descriptive Note:

Memorandum rept.,

Corporate Author:

MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB

Personal Author(s):

Report Date:

1987-11-01

Pagination or Media Count:

54.0

Abstract:

Abstract. This paper describes attempts to model the modules of early vision in terms of minimizing energy functions, in particular energy functions allowing discontinuities in the solution. It examines the success of using Hopfield-style analog networks for solving such problems. Finally it discusses the limitations of the energy function approach. Keywords Surface interpolation Motion smoothing Segmentation.

Subject Categories:

  • Bionics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE