Quality Assessment of Self-Calibration with Distortion Estimation for Grid Point Images
Paper in proceedings, 2014

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 high-fidelity 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.

Image Distortion

Gröbner basis

Performance Analysis

Bundle Adjustment

Planar Pattern

Self-Calibration

Author

Zlatko Franjcic

Chalmers, Applied Information Technology (Chalmers), Interaction Design (Chalmers)

Johan Bondeson

Qualisys AB

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

16821750 (ISSN)

Vol. XL-3 3 95-99

Areas of Advance

Information and Communication Technology

Subject Categories

Computer Vision and Robotics (Autonomous Systems)

DOI

10.5194/isprsarchives-XL-3-95-2014

More information

Latest update

5/30/2018