张钧
个人信息
Personal information
副教授 硕士生导师
性别:男
在职信息:在职
所在单位:人工智能与自动化学院
学历:研究生(博士)毕业
学位:工学博士学位
毕业院校:华中科技大学
学科:模式识别与智能系统
论文类型:期刊论文
第一作者:安培
通讯作者:张钧
合写作者:马杰,马滔,Bin Fang,Kun Yu,刘小茂
发表刊物:Journal of Optical Society of America A: Optics Image Science and Vision
收录刊物:SCI
学科门类:工学
一级学科:控制科学与工程
文献类型:J
卷号:38
期号:4
页面范围:504-514
DOI码:10.1364/JOSAA.414504
发表时间:2021-03-06
摘要:A zoom camera can change its focal length and track moving objects with an adjustable resolution. To extract
precise geometric information for the tracked objects, a zoom camera requires an accurate calibration method.
High-precision camera calibration methods, however, usually require a number of control points that are not guaranteed in some practical situations. Most zoom cameras suffer radial distortion. Athough a traditional method can
recover an undistorted image with known intrinsic parameters, it fails to work for a zoom camera with an unknown
focal length. Motivated by these problems, we propose a two-point calibration method (TPCM). In this scheme,
we first propose an approximate focal-invariant radial distortion (AFRD) model. With the AFRD model, an RGB
image can be undistorted with an unknown focal length. After that, the TPCM method is presented to estimate the
focal length and rotation matrix with only two control points for one image. Synthetic experiments demonstrate
that the AFRD model is efficient. In the real data experiment, the mean reprojection error of the TPCM method
is less than one pixel, which is smaller than current state-of-the-art methods, and we believe meets the demand for
high-precision calibration.