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Proceedings Paper

Recovering constrained model parameters from a monocular image
Author(s): Robert R. Goldberg
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Paper Abstract

In this paper active constraint set methods are applied with classical lagrange multiplier analysis to recover constrained model parameters from monocular images. Specific cases are shown from a number of complex models that demonstrate that the convergence process correctly recovers the original parameters from small amounts of matching data, relative to the large number of parameters and constraints describing the models. Application domains involved are real-time tracking of parametric models and calibration of vision equipment for factory settings.

Paper Details

Date Published: 1 November 1992
PDF: 12 pages
Proc. SPIE 1823, Machine Vision Applications, Architectures, and Systems Integration, (1 November 1992); doi: 10.1117/12.132088
Show Author Affiliations
Robert R. Goldberg, CUNY/Queens College (United States)

Published in SPIE Proceedings Vol. 1823:
Machine Vision Applications, Architectures, and Systems Integration
Bruce G. Batchelor; Susan Snell Solomon; Frederick M. Waltz, Editor(s)

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