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Self-Calibration of a 1D Projective Camera and Its Application to the Self-Calibration of a 2D Projective Camera
October 2000 (vol. 22 no. 10)
pp. 1179-1185

Abstract—We introduce the concept of self-calibration of a 1D projective camera from point correspondences, and describe a method for uniquely determining the two internal parameters of a 1D camera, based on the trifocal tensor of three 1D images. The method requires the estimation of the trifocal tensor which can be achieved linearly with no approximation unlike the trifocal tensor of 2D images and solving for the roots of a cubic polynomial in one variable. Interestingly enough, we prove that a 2D camera undergoing planar motion reduces to a 1D camera. From this observation, we deduce a new method for self-calibrating a 2D camera using planar motions. Both the self-calibration method for a 1D camera and its applications for 2D camera calibration are demonstrated on real image sequences.

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Index Terms:
Vision geometry, camera model, self-calibration, planar motion, 1D camera.
Citation:
Olivier Faugeras, Long Quan, Peter Strum, "Self-Calibration of a 1D Projective Camera and Its Application to the Self-Calibration of a 2D Projective Camera," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 10, pp. 1179-1185, Oct. 2000, doi:10.1109/34.879801
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