Robust Calibration of Cameras with Telephoto Lens Using Regularized Least Squares
Author(s) -
Mingpei Liang,
Xinyu Huang,
ChungHao Chen,
Gaolin Zheng,
Alade Tokuta
Publication year - 2014
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2014/689429
Subject(s) - focal length , computer vision , artificial intelligence , camera resectioning , regularization (linguistics) , calibration , camera lens , lens (geology) , computer science , camera auto calibration , mathematics , algorithm , optics , physics , statistics
Cameras with telephoto lens are usually used to recover details of an object that is either small or located far away from the cameras. However, the calibration of this kind of cameras is not as accurate as the one of cameras with short focal lengths that are commonly used in many vision applications. This paper has two contributions. First, we present a first-order error analysis that shows the relation between focal length and estimation uncertainties of camera parameters. To our knowledge, this error analysis with respect to focal length has not been studied in the area of camera calibration. Second, we propose a robust algorithm to calibrate the camera with a long focal length without using additional devices. By adding a regularization term, our algorithm makes the estimation of the image of the absolute conic well posed. As a consequence, the covariance of camera parameters can be reduced greatly. We further used simulations and real data to verify our proposed algorithm and obtained very stable results
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