Quality Assessment of Self-Calibration with Distortion Estimation for Grid Point Images

Recently, a camera self-calibration algorithm was reported which solves for pose, focal length and radial distortion using a minimal set of four 2D-to-3D point correspondences. In this paper, we present an empirical analysis of the algorithm’s accuracy using highfidelity point correspondences. In pa...

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Bibliographic Details
Main Authors: Franjcic, Z., Bondeson, J.
Format: Conference Proceeding
Language:English
Subjects:
Bundle Adjustment
Gröbner basis
Image Distortion
Performance Analysis
Planar Pattern
Self-Calibration
Online Access:Get full text
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Summary:Recently, a camera self-calibration algorithm was reported which solves for pose, focal length and radial distortion using a minimal set of four 2D-to-3D point correspondences. In this paper, we present an empirical analysis of the algorithm’s accuracy using highfidelity point correspondences. In particular, we use images of circular markers arranged in a regular planar grid, obtain the centroids of the marker images, and pass those as input point correspondences to the algorithm. We compare the resulting reprojection errors against those obtained from a benchmark calibration based on the same data. Our experiments show that for low-noise point images the self-calibration technique performs at least as good as the benchmark with a simplified distortion model.
ISSN:2194-9034
1682-1750
2194-9034
DOI:10.5194/isprsarchives-XL-3-95-2014