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Accurate features point extraction for omnidirectional camera calibration
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Paper Abstract

The distorted checkerboard image affects the precision calibration in omnidirectional camera calibration due to inaccurate localization of features points. To solve this problem, an iterative refinement method is presented. Firstly, the initial-parameters are obtained from the traditional calibration method and the distorted checkerboard images are corrected to world coordinate system. Then, the features points are located in those undistorted images. The calibration parameters are recomputed in an iterative refinement until convergence. This iterative refinement method improves localization accuracy of feature points and consequently of camera calibration. The correctness and effectiveness of the method is proved by simulation experiments and physical experiments. The experiments show that the rep rojection error is reduced by 38% compared to traditional methods.

Paper Details

Date Published: 14 August 2019
PDF: 5 pages
Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111792J (14 August 2019); doi: 10.1117/12.2539870
Show Author Affiliations
Xuanrui Gong, Changchun Univ. of Science and Technology (China)
Yaowen Lv, Changchun Univ. of Science and Technology (China)
Zicheng Xu, Changchun Univ. of Science and Technology (China)
Zhaoguo Jiang, Changchun Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 11179:
Eleventh International Conference on Digital Image Processing (ICDIP 2019)
Jenq-Neng Hwang; Xudong Jiang, Editor(s)

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