Proceedings of the conference on Visualization '01
ACM SIGGRAPH 2003 Papers
Fairing of Point Based Surfaces
CGI '04 Proceedings of the Computer Graphics International
A New Bilateral Mesh Smoothing Method by Recognizing Features
CAD-CG '05 Proceedings of the Ninth International Conference on Computer Aided Design and Computer Graphics
Anisotropic smoothing of point sets
Computer Aided Geometric Design - Special issue: Geometric modelling and differential geometry
A dynamic balanced flow for filtering point-sampled geometry
The Visual Computer: International Journal of Computer Graphics
Robust Smooth Feature Extraction from Point Clouds
SMI '07 Proceedings of the IEEE International Conference on Shape Modeling and Applications 2007
Post-processing of scanned 3D surface data
SPBG'04 Proceedings of the First Eurographics conference on Point-Based Graphics
On normals and projection operators for surfaces defined by point sets
SPBG'04 Proceedings of the First Eurographics conference on Point-Based Graphics
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Based on sampling likelihood and feature intensity, in this paper, a feature-preserving denoising algorithm for point-sampled surfaces is proposed. In terms of moving least squares surface, the sampling likelihood for each point on point-sampled surfaces is computed, which measures the probability that a 3D point is located on the sampled surface. Based on the normal tensor voting, the feature intensity of sample point is evaluated. By applying the modified bilateral filtering to each normal, and in combination with sampling likelihood and feature intensity, the filtered point-sampled surfaces are obtained. Experimental results demonstrate that the algorithm is robust, and can denoise the noise efficiently while preserving the surface features.