Mesh Total Generalized Variation for Denoising [paper]
โกStatus Update: [2021/06/08] This paper has been accepted by the IEEE Transactions on Visualization and Computer Graphics (TVCG).
by Zheng Liu, Yanlei Li, Weina Wang, Ligang Liu, and Renjie Chen(Corresponding author)
MeshTGV is an efficient numerical framework to discretize TGV over triangular meshes. Based on this discretization, a vectorial TGV regularization model is proposed to restore the face normal field. Then, we introduce an efficient and effective algorithm to solve the optimization problem.
MeshTGV
โ
โโโ data [//comparison data used in our paper]
โ โโโ CAD
โ โโโ Kinect
โ โโโ NonCAD
โ
โโโ MeshTGV-1.2.0.exe [//executable file to run our algorithm]
โโโ README.md
-
double click the executable file.
-
load a mesh file (.obj) :
Menu
โModel
โLoad Mesh
โChoose your noisy mesh
-
open the MeshTGV algorithm panel :
Menu
โDenoising
โMeshTGV
-
set parameters then click the
Run
button. -
get output :
- Visualization output : showed in the mainwindow.
- Norm result output : automaticlly saved in the same folder with the input Noisy Mesh.
- Mesh result output : You need to save the Mesh result manually :
Menu
โModel
โSave
Please see Section 6.1 Parameters Setting
in our paper for more details of parameters.
There are four files in each model's folder. For example, in Block's folder :
data [//comparison data used in our paper]
โโโ CAD
โ โโโ Block
โ โ โโโ groundtruth.obj
โ โ โโโ noisy.obj
โ โ โโโ tgv_filtered_normals-aad=xxx.txt
โ โ โโโ tgv_result_mesh.obj
โ โโโ ...
โ
โโโ Kinect
โโโ NonCAD
-
groundtruth.obj
: The GroundTruth data of model. -
noisy.obj
: The Noise data of model. -
tgv_filtered_normals-aad=xxx.txt
: The result normals saved after MeshTGV Normal Filtering but before Vertex Updating. "aad=xxx" in the filename means the Average Angle Deviation(ฮธ) of the result normals is "xxx". -
tgv_result_mesh.obj
: The result mesh saved after MeshTGV Normal Filtering and Vertex Updating.
If you find this work helpful please consider citing it :
@article{Liu2021MeshTGV,
title={Mesh Total Generalized Variation for Denoising},
author={Liu, Zheng and Li, Yanlei and Wang, Weina and Liu, Ligang and Chen, Renjie},
journal={IEEE Transactions on Visualization and Computer Graphics},
year={2021},
doi={10.1109/TVCG.2021.3088118},
}