The Nonparametric Approach for Camera Calibration
Abstract
Discusses a nonparametric approach for calibrating a CCD camera, a constrained topological mapping (CTM) approach to analyze the systematic imaging errors of an image system and compare it with parametric approaches which are based on optimization and have been discussed by many other authors. This nonparametric approach has several distinct features. In this approach, some distortion surfaces are derived directly from the training samples. Because no analytical form of these surfaces is assumed, when we modeled the distortions by a nonparametric model, the systematic imaging errors instead of mere lens distortions are considered. This gives an new approach to analyze the imaging errors of a particular imaging system. Experimental results are given in detail, which indicate that both in image projection and in 3D reconstruction, the accuracy is much improved when the nonparametric approach is employed for calibrating a camera.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Cite
Text
Qiu and De Ma. "The Nonparametric Approach for Camera Calibration." IEEE/CVF International Conference on Computer Vision, 1995. doi:10.1109/ICCV.1995.466782Markdown
[Qiu and De Ma. "The Nonparametric Approach for Camera Calibration." IEEE/CVF International Conference on Computer Vision, 1995.](https://mlanthology.org/iccv/1995/qiu1995iccv-nonparametric/) doi:10.1109/ICCV.1995.466782BibTeX
@inproceedings{qiu1995iccv-nonparametric,
title = {{The Nonparametric Approach for Camera Calibration}},
author = {Qiu, MaoLin and De Ma, Song},
booktitle = {IEEE/CVF International Conference on Computer Vision},
year = {1995},
pages = {224-229},
doi = {10.1109/ICCV.1995.466782},
url = {https://mlanthology.org/iccv/1995/qiu1995iccv-nonparametric/}
}