Robust algebraic invariant methods with applications in geometry and imaging

Eamon B. Barrett; Paul Max Payton; Gregory O. Gheen

doi:10.1117/12.216941

23 August 1995 Robust algebraic invariant methods with applications in geometry and imaging

Eamon B. Barrett, Paul Max Payton, Gregory O. Gheen

Proceedings Volume 2572, Remote Sensing and Reconstruction for Three-Dimensional Objects and Scenes; (1995) https://doi.org/10.1117/12.216941
Event: SPIE's 1995 International Symposium on Optical Science, Engineering, and Instrumentation, 1995, San Diego, CA, United States

Abstract

We introduce non-standard methods of deriving algebraic invariants and demonstrated two types of applications of these invariants. In model transfer a collection of conjugate points are determined on a set of reference images, and `transferred' to the matching conjugate points on a new view of the 3D object, without prior computation of camera geometry or scene reconstruction. In object reconstruction, general 3D object points are represented as functions of non-coplanar fiducial points and corresponding conjugate points across multiple images. In this application the object points are `reconstructed' once quantitative values are specified for the fiducial points. The methods we introduce for deriving these invariant algorithms are extensible from the linear fractional central projection camera model to weak perspective and certain non-central projection camera models. Stability to adverse geometries and measurement error can be enhanced by using redundant fiducial points and images to determine the transfer and reconstruction functions. Extensibility and stability are indications of the robustness of these methods.

Citation Download Citation

Eamon B. Barrett, Paul Max Payton, and Gregory O. Gheen "Robust algebraic invariant methods with applications in geometry and imaging", Proc. SPIE 2572, Remote Sensing and Reconstruction for Three-Dimensional Objects and Scenes, (23 August 1995); https://doi.org/10.1117/12.216941

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