Recovering constrained model parameters from a monocular image

Robert R. Goldberg

doi:10.1117/12.132088

1 November 1992 Recovering constrained model parameters from a monocular image

Robert R. Goldberg

Proceedings Volume 1823, Machine Vision Applications, Architectures, and Systems Integration; (1992) https://doi.org/10.1117/12.132088
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States

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.

Citation Download Citation

Robert R. Goldberg "Recovering constrained model parameters from a monocular image", Proc. SPIE 1823, Machine Vision Applications, Architectures, and Systems Integration, (1 November 1992); https://doi.org/10.1117/12.132088

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