Paper
17 August 1994 Relative orientation of image triples using straight linear features
Elli Petsa, Petros G. Patias
Author Affiliations +
Proceedings Volume 2357, ISPRS Commission III Symposium: Spatial Information from Digital Photogrammetry and Computer Vision; (1994) https://doi.org/10.1117/12.182907
Event: Spatial Information from Digital Photogrammetry and Computer Vision: ISPRS Commission III Symposium, 1994, Munich, Germany
Abstract
Linear features abound in man-made environments and the possibility of their automated detection and measurement on digital images renders their employment -- rather than that of point features -- highly advantageous for camera calibration, space resection, relative orientation and object reconstruction, particularly in close-range photogrammetry and computer vision. This paper presents our formulation and treatment of mathematical models suitable for the tasks of relative orientation of image triples and for object reconstruction, up to a scale factor, from straight line correspondences, a problem known as `motion and structure' in computer vision. In this phase, the formulated algorithms have been extensively investigated with simulations employing various basic line configurations in order to further illuminate the still inadequately addressed questions of critical geometries and degeneracy. Conclusions are reported for several degenerate combinations of object line distributions and perspective center position patterns which have a particular interest. Finally, a simulated numerical example is also given.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Elli Petsa and Petros G. Patias "Relative orientation of image triples using straight linear features", Proc. SPIE 2357, ISPRS Commission III Symposium: Spatial Information from Digital Photogrammetry and Computer Vision, (17 August 1994); https://doi.org/10.1117/12.182907
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Cited by 3 scholarly publications.
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KEYWORDS
Photogrammetry

Computer vision technology

Machine vision

Cameras

Reconstruction algorithms

Mathematical modeling

Systems modeling

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