Recently, self-calibration algorithms that use only the
information in the image have been actively researched.
But most algorithms require bundle adjustment in the
projective reconstruction or in the nonlinear minimization.
We propose a practical self-calibration algorithm that only
requires a linear projective reconstruction. We overcome
the sensitivity of the algorithm due to image noises by
adding another constraint on the principal point. Also we
propose a variant of linear auto-calibration algorithm
which uses the similar assumption of the work of [9],
based on the property of the absolute quadric.
Experimental results using real and synthetic images
demonstrate the feasibility of the proposed algorithm.