Abstract

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.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.