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Proceedings Paper

Feature entity least squares matching: a technique for the automatic control of imagery
Author(s): Urho A. Rauhala; Walter J. Mueller
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Paper Abstract

Nonlinear modeling and solution techniques of array algebra are applied to the problem of simultaneous graph matching and photogrammetric bundle adjustment. Graph matching provides automatically the image coordinates and 2 X 2 weight matrices of `control entities', points and vertices of known relative geometrical shape which replace the control points used in traditional bundle adjustment. Inclusion of multiple control entities to cover the entire image area of interest allows the use of a fast new array algebra formation of real-time bundle adjustment to act as the pull-in mechanism for the global graph matching process. The resulting integrated solution of Feature Entity Least Squares Matching (FELSM) is very fast and produces high quality results. FELSM has demonstrated solutions to several problems of ongoing research interest in photogrammetry and the related fields of image understanding, pattern recognition and computer vision. These results open the way for further integration of the various fields.

Paper Details

Date Published: 5 July 1995
PDF: 14 pages
Proc. SPIE 2486, Integrating Photogrammetric Techniques with Scene Analysis and Machine Vision II, (5 July 1995); doi: 10.1117/12.213132
Show Author Affiliations
Urho A. Rauhala, GDE Systems, Inc. (United States)
Walter J. Mueller, GDE Systems, Inc. (United States)


Published in SPIE Proceedings Vol. 2486:
Integrating Photogrammetric Techniques with Scene Analysis and Machine Vision II
David M. McKeown; Ian J. Dowman, Editor(s)

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