Model Based Pose Estimation of Articulated and Constrained Objects
Abstract
This paper presents a method for localization of modeled objects that is general enough to cover articulated and other types of constrained models. The flexibility between components of the model are expressed as spatial constraints which are fused into the pose estimation process. The constraint fusion assists in obtaining a precise and stable pose of each object's component and in finding the correct interpretation. The proposed method can handle any constraint (including inequalities) between any number of different components of the model. The framework is based on Kalman filtering.
Cite
Text
Hel-Or and Werman. "Model Based Pose Estimation of Articulated and Constrained Objects." European Conference on Computer Vision, 1994. doi:10.1007/3-540-57956-7_31Markdown
[Hel-Or and Werman. "Model Based Pose Estimation of Articulated and Constrained Objects." European Conference on Computer Vision, 1994.](https://mlanthology.org/eccv/1994/helor1994eccv-model/) doi:10.1007/3-540-57956-7_31BibTeX
@inproceedings{helor1994eccv-model,
title = {{Model Based Pose Estimation of Articulated and Constrained Objects}},
author = {Hel-Or, Yacov and Werman, Michael},
booktitle = {European Conference on Computer Vision},
year = {1994},
pages = {262-273},
doi = {10.1007/3-540-57956-7_31},
url = {https://mlanthology.org/eccv/1994/helor1994eccv-model/}
}