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Decomposition of transformation matrices for robot vision
Abstract
The relationship between the three-dimensional coordinates of a point and the corresponding two-dimensional coordinates of its image, as seen by a camera, can be expressed in terms of a 3 by 4 matrix using the homogeneous coordinate system. This matrix is known more generally as the transformation matrix and can be determined experimentaily by measuring the image coordinates of six or more known paoints in space. Such a transformation can also be derived analytically from knowledge of the camera position, orientation, focal length and scaling and translation parameters in the image plane. However, the inverse problem of computing the camera location and orientation from the transformation matrix involves solution of simultaneous nonlinear equations in several variables and is considered difficult. In this paper we present a new and simple analytical technique that accomplishes this inversion rather easily. This technique works very well in practice and has considerable applications for motion tracking.
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Fischler, M. A., & Bolles, R. C. (1981) · Communications of the ACM · doi:10.1145/358669.358692 · Cited by 25,893
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Ansar, A., & Daniilidis, K. (2003) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2003.1195992 · Cited by 434
(2002) · Cited by 200
Metadata
- Authors
- Ganapathy, S.
- Venue
- Proceedings. 1984 IEEE International Conference on Robotics and Automation
- Published
- 2005-03-23
- Volume
- 1
- Pages
- 130-139
- ISSN
- 1050-4729 (ISSN-L)
- OpenAlex
- W2122928074
- Cited by
- 246
- References
- 1
- FWCI
- 11.20
- Type
- conference paper
- Language
- en
- Open access
- closed
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