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Proceedings Paper

View-based methods for relative reconstruction of 3D scenes from several 2D images
Author(s): Eamon B. Barrett; Paul Max Payton; Peter J. Marra; Michael H. Brill
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Paper Abstract

Suppose we have two or more images of a 3D scene. From these views alone, we would like to infer the (x,y,z) coordinates of the object-points in the scene (to reconstruct the scene). The most general standard methods require either prior knowledge of the camera models (intersection methods) or prior knowledge of the (x,y,z) coordinates of some of the object points, from which the camera models can be inferred (resection, followed by intersection). When neither alternative is available, a special technique called relative orientation enables a scale model of a scene to be reconstructed from two images, but only when the internal parameters of both cameras are identical. In this paper, we discuss alternatives to relative orientation that does not require knowledge of the internal parameters of the imaging systems. These techniques, which we call view- based relative reconstruction, determine the object-space coordinates up to a 3D projective transformation. The reconstructed points are then exemplars of a projective orbit of representations that are chosen to reside in a particular representation called a canonical frame. Two strategies will be described to choose this canonical frame: (1) projectively simplify the object model and the imaging equations; and (2) projectively simplify the camera model and the imaging equations. In each case, we solve the resulting simplified system of imaging equations to retrieve exemplar points. Both strategies are successful in synthetic imagery, but may be differently suited to various real-world applications.

Paper Details

Date Published: 30 July 1998
PDF: 14 pages
Proc. SPIE 3364, Enhanced and Synthetic Vision 1998, (30 July 1998); doi: 10.1117/12.317485
Show Author Affiliations
Eamon B. Barrett, Lockheed Martin Missiles & Space (United States)
Paul Max Payton, Lockheed Martin Missiles & Space (United States)
Peter J. Marra, Lockheed Martin Missiles & Space (United States)
Michael H. Brill, Sarnoff Corp. (United States)

Published in SPIE Proceedings Vol. 3364:
Enhanced and Synthetic Vision 1998
Jacques G. Verly, Editor(s)

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