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Proceedings Paper

Adaptive Least Squares Correlation With Geometrical Constraints
Author(s): Armin W. Gruen; Emmanuel P. Baltsavias
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Paper Abstract

The Adaptive Least Squares Correlation is a general and flexible technique for many different image matching problems. It allows for simultaneous local geometrical image shaping and radiometric corrections, whereby the system parameters are automatically assessed, corrected and thus optimized with respect to the specific signal during the least squares iterations. Precision and reliability measures can be developed to assess the quality of the match. A stabilization and improvement of the correlation procedure can be achieved through the simultaneous consideration of object point intersection conditions from conjugate rays and other sensor and object constraints. These geometrical constraints limit the search area size, reduce the number of alternatives, increase the precision and reliability of matching and provide simultaneously 3D-point positioning information. The method can be applied to correlation, object detection and measurement, and image tracking, while the 3D-information provided can be readily utilized for tasks requiring inspection, manipulation, object tracking and navigation. As an exciting new prospect the method can be applied to more than two images at a time. This paper outlines the basic concept of the technique.

Paper Details

Date Published: 9 June 1986
PDF: 11 pages
Proc. SPIE 0595, Computer Vision for Robots, (9 June 1986); doi: 10.1117/12.952246
Show Author Affiliations
Armin W. Gruen, Federal Institute of Technology (Switzerland)
Emmanuel P. Baltsavias, Federal Institute of Technology (Switzerland)


Published in SPIE Proceedings Vol. 0595:
Computer Vision for Robots
Olivier D. Faugeras; Robert B. Kelley, Editor(s)

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