A Self-Calibration Method for Smart Video Cameras
Abstract
The automatic calibration of the intrinsic camera parameters such as the focal length and the camera orientation is an important pre-requisite for many computer vision algorithms in video surveillance. Despite its importance only a few number of methods show their applicability in embedded systems. This paper shows new results of previous work done in camera self-calibration on images of the York Urban data-set. These 102 images show typical urban scenes one might expect in practice. The evaluation shows that in 52 of 102 images the proposed method achieves less than 5% relative error in the focal length at a mean computation time per image of 14.45 s on a standard PC. We believe that these results show a fair balance between accuracy and computational performance and encourage an embedded implementation on a smart camera.
Cite
Text
Nebehay and Pflugfelder. "A Self-Calibration Method for Smart Video Cameras." IEEE/CVF International Conference on Computer Vision Workshops, 2009. doi:10.1109/ICCVW.2009.5457614Markdown
[Nebehay and Pflugfelder. "A Self-Calibration Method for Smart Video Cameras." IEEE/CVF International Conference on Computer Vision Workshops, 2009.](https://mlanthology.org/iccvw/2009/nebehay2009iccvw-selfcalibration/) doi:10.1109/ICCVW.2009.5457614BibTeX
@inproceedings{nebehay2009iccvw-selfcalibration,
title = {{A Self-Calibration Method for Smart Video Cameras}},
author = {Nebehay, Georg and Pflugfelder, Roman P.},
booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
year = {2009},
pages = {840-846},
doi = {10.1109/ICCVW.2009.5457614},
url = {https://mlanthology.org/iccvw/2009/nebehay2009iccvw-selfcalibration/}
}