Denoising of Point-clouds Based on Structured Dictionary Learning

Sarkar, Kripasindhu; Bernard, Florian; Varanasi, Kiran; Theobalt, Christian; Stricker, Didier

Denoising of Point-clouds Based on Structured Dictionary Learning

Files

005-006.pdf (6.14 MB)

Date

2018

Authors

Sarkar, Kripasindhu
Bernard, Florian
Varanasi, Kiran
Theobalt, Christian
Stricker, Didier

Publisher

The Eurographics Association

Abstract

We formulate the problem of point-cloud denoising in terms of a dictionary learning framework over square surface patches. Assuming that many of the local patches (in the unknown noise-free point-cloud) contain redundancies due to surface smoothness and repetition, we estimate a low-dimensional affine subspace that (approximately) explains the extracted noisy patches. This is achieved via a structured low-rank matrix factorization that imposes smoothness on the patch dictionary and sparsity on the coefficients. We show experimentally that our method outperforms existing denoising approaches in various noise scenarios.

        @inproceedings{10.2312:sgp.20181180
,
booktitle = {Symposium on Geometry Processing 2018- Posters
},
editor = {Ju, Tao and Vaxman, Amir
},
title = {{Denoising of Point-clouds Based on Structured Dictionary Learning
}},
author = {Sarkar, Kripasindhu and 
Bernard, Florian and 
Varanasi, Kiran and 
Theobalt, Christian and 
Stricker, Didier
},
year = {2018
},
publisher = {The Eurographics Association
},
ISSN = {1727-8384
},
ISBN = {978-3-03868-069-7
},
DOI = {10.2312/sgp.20181180
}
}