Implicit Surface Reconstruction from Scattered Point Data with Noise

Authors:
Jun Yang;Zhengning Wang;Changqian Zhu;Qiang Peng
Affiliations:
School of Information Science & Technology Southwest Jiaotong, University, Chengdu, Sichuan 610031, China and School of Mechanical & Electrical Engineering Lanzhou Jiaotong, University, Lanzhou, G ...;School of Information Science & Technology Southwest Jiaotong, University, Chengdu, Sichuan 610031, China;School of Information Science & Technology Southwest Jiaotong, University, Chengdu, Sichuan 610031, China;School of Information Science & Technology Southwest Jiaotong, University, Chengdu, Sichuan 610031, China
Venue:
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part II
Year:
2007

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Abstract

This paper addresses the problem of reconstructing implicit function from point clouds with noise and outliers acquired with 3D scanners. We introduce a filtering operator based on mean shift scheme, which shift each point to local maximum of kernel density function, resulting in suppression of noise with different amplitudes and removal of outliers. The "clean" data points are then divided into subdomains using an adaptive octree subdivision method, and a local radial basis function is constructed at each octree leaf cell. Finally, we blend these local shape functions together with partition of unity to approximate the entire global domain. Numerical experiments demonstrate robust and high quality performance of the proposed method in processing a great variety of 3D reconstruction from point clouds containing noise and outliers.