Accession Number:

ADA218170

Title:

Stereo Feature Matching in Disparity Space

Descriptive Note:

Memorandum rept.

Corporate Author:

MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB

Personal Author(s):

Report Date:

1989-09-01

Pagination or Media Count:

22.0

Abstract:

This paper describes a new method for matching, validating, and disambiguating features for stereo vision. It is based on the Marr-Poggio- Grimson stereo matching algorithm which uses zero-crossing contours in difference of Gaussian filtered images as features. The matched contours are represented in disparity space, which makes the information needed for matched contour validation and disambiguation easily accessible. The use of disparity space also makes the algorithm conceptually cleaner than previous implementations of the Marr-Poggio-Grimson algorithm and yields a more efficient matching process. Keywords Stereo vision Artificial intelligence Algorithms Stereo matching Disparity space.

Subject Categories:

  • Cybernetics
  • Navigation and Guidance

Distribution Statement:

APPROVED FOR PUBLIC RELEASE