Spatio-temporal Upsampling for Free Viewpoint Video Point Clouds
Matthew Moynihan, Rafael Pagés, Aljosa Smolic
2019
Abstract
This paper presents an approach to upsampling point cloud sequences captured through a wide baseline camera setup in a spatio-temporally consistent manner. The system uses edge-aware scene flow to understand the movement of 3D points across a free-viewpoint video scene to impose temporal consistency. In addition to geometric upsampling, a Hausdorff distance quality metric is used to filter noise and further improve the density of each point cloud. Results show that the system produces temporally consistent point clouds, not only reducing errors and noise but also recovering details that were lost in frame-by-frame dense point cloud reconstruction. The system has been successfully tested in sequences that have been captured via both static or handheld cameras.
DownloadPaper Citation
in Harvard Style
Moynihan M., Pagés R. and Smolic A. (2019). Spatio-temporal Upsampling for Free Viewpoint Video Point Clouds. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP; ISBN 978-989-758-354-4, SciTePress, pages 684-692. DOI: 10.5220/0007361606840692
in Bibtex Style
@conference{visapp19,
author={Matthew Moynihan and Rafael Pagés and Aljosa Smolic},
title={Spatio-temporal Upsampling for Free Viewpoint Video Point Clouds},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP},
year={2019},
pages={684-692},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007361606840692},
isbn={978-989-758-354-4},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP
TI - Spatio-temporal Upsampling for Free Viewpoint Video Point Clouds
SN - 978-989-758-354-4
AU - Moynihan M.
AU - Pagés R.
AU - Smolic A.
PY - 2019
SP - 684
EP - 692
DO - 10.5220/0007361606840692
PB - SciTePress