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Erschienen in:
2008 | OriginalPaper | Buchkapitel
Implicit Surface Reconstruction with Radial Basis Functions
verfasst von : Jun Yang, Zhengning Wang, Changqian Zhu, Qiang Peng
Erschienen in: Computer Vision and Computer Graphics. Theory and Applications
Verlag: Springer Berlin Heidelberg
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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.