Automated relative orientation modeling using feature matching

Liang-Chien Chen

doi:10.1117/12.2294363

1 August 1990 Automated relative orientation modeling using feature matching

Liang-Chien Chen

Proceedings Volume 1395, Close-Range Photogrammetry Meets Machine Vision; 13953C (1990) https://doi.org/10.1117/12.2294363
Event: Close-Range Photogrammetry Meets Machine Vision, 1990, Zurich, Switzerland

Abstract

This paper deals with using feature-based matching, FBM, to automatically accomplish the correspondence for conjugate points in a stereopair then to determine the relative orientation parameters. The approach includes : (1) coarse matching between a reduced image pairs by FBM to determine the affine transformation coefficients for patch prediction, (2) matching critical points in the corresponded patches, and (3) calculating relative orientation parameters and performing consistency check. In the first two steps, FBM is applied. Which includes (1) convolving each image with a Laplacian of Gaussian, LoG, mask, (2) vectorizing the zero crossing image, (3) performing line approximation to extract critical points, and (4) similarity assessment. An aerial stereopair was used in the case study. To improve the matching accuracy, the refinement for the image correspondence by area-based matching, ABM, is also studied. The results indicate that the RMS of Y-parallax is 0.8 pixels by FBM and is 0.25 pixels after the correspondence refinement.

Citation Download Citation

Liang-Chien Chen "Automated relative orientation modeling using feature matching", Proc. SPIE 1395, Close-Range Photogrammetry Meets Machine Vision, 13953C (1 August 1990); https://doi.org/10.1117/12.2294363

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available