Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
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SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
A volumetric method for building complex models from range images
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SUSAN—A New Approach to Low Level Image Processing
International Journal of Computer Vision
Implicit surface-based geometric fusion
Computer Vision and Image Understanding - Special issue on CAD-based computer vision
Implicit fairing of irregular meshes using diffusion and curvature flow
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Feature sensitive surface extraction from volume data
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
A complete distance field representation
Proceedings of the conference on Visualization '01
Simplification and Repair of Polygonal Models Using Volumetric Techniques
IEEE Transactions on Visualization and Computer Graphics
Smoothing Of Three Dimensional Models By Convolution
CGI '96 Proceedings of the 1996 Conference on Computer Graphics International
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VIS '04 Proceedings of the conference on Visualization '04
SUSAN structure preserving filtering for mesh denoising
The Visual Computer: International Journal of Computer Graphics
SGP '05 Proceedings of the third Eurographics symposium on Geometry processing
A new vector field distance transform and its application to mesh processing from 3D scanned data
The Visual Computer: International Journal of Computer Graphics
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This paper addresses the problem of feature preserving mesh filtering, which occurs in surface reconstruction of scanned objects, which include acquisition noise to be removed without altering sharp edges. We propose a method based on a vector field distance transform of the mesh to process. It is a volume-based implicit surface modeling, which provides an alternative representation of meshes. We use an adaptive 3D convolution kernel applied to the voxels of the distance transform model. Weights of the kernel elements are determined according to the angle between the vectors of the implicit field. We also propose a new adaptation of the Marching Cubes algorithm in order to extract the isosurface from the vector implicit field after the filtering process. We compare our method to the previous one introduced using the vector field representation and to other feature preserving adaptive filtering algorithms. According to error metric evaluations, we show that our new design provides high quality filtering results while better preserving geometric features.