POINT CLOUD DENOISING USING ROBUST PRINCIPAL COMPONENT ANALYSIS

Esmeide A. Leal Narváez, Nallig Eduardo Leal Narváez

2006

Abstract

This paper presents a new method for filtering noise occurring in point cloud sampled data. The method smoothes the data set whereas preserves sharp features. We propose a new weighted variant of the principal component analysis method, which instead of using exponential weighting factors inversely proportional to the Euclidean distance to the mean, which is computationally expensive, uses weighting factors assignment by inversely proportional repartition of the sum of distance to the mean. The determination of weighted factors by means of inverse proportional repartition makes our variant robust to outliers. Additionally, we propose a simple solution to the problem of data shrinkage produced by the linear local fitting of the principal component analysis. The proposed method is simple, easy to implement, and effective for noise filtering.

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Paper Citation


in Harvard Style

A. Leal Narváez E. and Eduardo Leal Narváez N. (2006). POINT CLOUD DENOISING USING ROBUST PRINCIPAL COMPONENT ANALYSIS . In Proceedings of the First International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, ISBN 972-8865-39-2, pages 51-58. DOI: 10.5220/0001358900510058


in Bibtex Style

@conference{grapp06,
author={Esmeide A. Leal Narváez and Nallig Eduardo Leal Narváez},
title={POINT CLOUD DENOISING USING ROBUST PRINCIPAL COMPONENT ANALYSIS},
booktitle={Proceedings of the First International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP,},
year={2006},
pages={51-58},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001358900510058},
isbn={972-8865-39-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP,
TI - POINT CLOUD DENOISING USING ROBUST PRINCIPAL COMPONENT ANALYSIS
SN - 972-8865-39-2
AU - A. Leal Narváez E.
AU - Eduardo Leal Narváez N.
PY - 2006
SP - 51
EP - 58
DO - 10.5220/0001358900510058