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Content Provider | IEEE Xplore Digital Library |
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Author | Dunne, A.K. Mallon, J. Whelan, P.F. |
Copyright Year | 2007 |
Description | Author affiliation: Dublin City Univ., Dublin (Dunne, A.K.; Mallon, J.; Whelan, P.F.) |
Abstract | Generic camera calibration is a non-parametric calibration technique that is applicable to any type of vision sensor. However, the standard generic calibration method was developed with the goal of generality and it is therefore sub-optimal for the common case of cameras with a single centre of projection (e.g. pinhole, fisheye, hyperboloidal catadioptric). This paper proposes novel improvements to the standard generic calibration method for central cameras that reduce its complexity, and improve its accuracy and robustness. Improvements are achieved by taking advantage of the geometric constraints resulting from a single centre of projection. Input data for the algorithm is acquired using active grids, the performance of which is characterised. A new linear estimation stage to the generic algorithm is proposed incorporating classical pinhole calibration techniques, and it is shown to be significantly more accurate than the linear estimation stage of the standard method. A linear method for pose estimation is also proposed and evaluated against the existing polynomial method. Distortion correction and motion reconstruction experiments are conducted with real data for a hyperboloidal catadioptric sensor for both the standard and proposed methods. Results show the accuracy and robustness of the proposed method to be superior to those of the standard method. |
Starting Page | 1 |
Ending Page | 8 |
File Size | 644774 |
Page Count | 8 |
File Format | |
ISBN | 9781424416301 |
ISSN | 15505499 |
DOI | 10.1109/ICCV.2007.4408990 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2007-10-14 |
Publisher Place | Brazil |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Calibration Cameras Lenses Robustness Polynomials Machine vision Sensor systems Standards development Image reconstruction Pixel |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition Software |
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