A Two-Stage Robust Statistical Method for Temporal Registration from Features of Various Type
Abstract
A model registration system capable of tracking an object, the model of which is known, in an image sequence is presented. It integrates tracking, pose determination and updating of the visible features. The heart of our system is the pose computation method, which handles various features (points, lines and free-form curves) in a very robust way and is able to give a correct estimate of the pose even when tracking errors occur. The reliability of the system is shown on an augmented reality project.
Cite
Text
Simon and Berger. "A Two-Stage Robust Statistical Method for Temporal Registration from Features of Various Type." IEEE/CVF International Conference on Computer Vision, 1998. doi:10.1109/ICCV.1998.710728Markdown
[Simon and Berger. "A Two-Stage Robust Statistical Method for Temporal Registration from Features of Various Type." IEEE/CVF International Conference on Computer Vision, 1998.](https://mlanthology.org/iccv/1998/simon1998iccv-two/) doi:10.1109/ICCV.1998.710728BibTeX
@inproceedings{simon1998iccv-two,
title = {{A Two-Stage Robust Statistical Method for Temporal Registration from Features of Various Type}},
author = {Simon, Gilles and Berger, Marie-Odile},
booktitle = {IEEE/CVF International Conference on Computer Vision},
year = {1998},
pages = {261-266},
doi = {10.1109/ICCV.1998.710728},
url = {https://mlanthology.org/iccv/1998/simon1998iccv-two/}
}