Linking Pose and Motion
Abstract
Algorithms designed to estimate 3D pose in video sequences enforce temporal consistency but typically overlook an important source of information: The 3D pose of an object, be it rigid or articulated, has a direct influence on its direction of travel. In this paper, we use the cases of an airplane performing aerobatic maneuvers and of pedestrians walking and turning to demonstrate that this information can and should be used to increase the accuracy and reliability of pose estimation algorithms.
Cite
Text
Fossati and Fua. "Linking Pose and Motion." European Conference on Computer Vision, 2008. doi:10.1007/978-3-540-88693-8_15Markdown
[Fossati and Fua. "Linking Pose and Motion." European Conference on Computer Vision, 2008.](https://mlanthology.org/eccv/2008/fossati2008eccv-linking/) doi:10.1007/978-3-540-88693-8_15BibTeX
@inproceedings{fossati2008eccv-linking,
title = {{Linking Pose and Motion}},
author = {Fossati, Andrea and Fua, Pascal},
booktitle = {European Conference on Computer Vision},
year = {2008},
pages = {200-213},
doi = {10.1007/978-3-540-88693-8_15},
url = {https://mlanthology.org/eccv/2008/fossati2008eccv-linking/}
}