Nowadays, computer vision has been wildly used in our daily life. In order to get some reliable information, camera
calibration can not be neglected. Traditional camera calibration cannot be used in reality due to the fact that
we cannot find the accurate coordinate information of the referenced control points. In this article, we present a
camera calibration algorithm which can determine the intrinsic parameters both with the extrinsic parameters.
The algorithm is based on the parallel lines in photos which can be commonly find in the real life photos. That
is we can first get the intrinsic parameters as well as the extrinsic parameters though the information picked
from the photos we take from the normal life. More detail, we use two pairs of the parallel lines to compute
the vanishing points, specially if these parallel lines are perpendicular, which means these two vanishing points
are conjugate with each other, we can use some views (at least 5 views) to determine the image of the absolute
conic(IAC). Then, we can easily get the intrinsic parameters by doing cholesky factorization on the matrix of
IAC.As we all know, when connect the vanishing point with the camera optical center, we can get a line which is
parallel with the original lines in the scene plane. According to this, we can get the extrinsic parameters R and
T. Both the simulation and the experiment results meets our expectations.