Mesh Detail Editing by Filtering Differential Edge Coordinates

In this paper, we propose anovel geometricaldetail editing method for triangulatedmeshmodels based on filtering robust differential edge coordinates.Theintroduceddetail editing consists ofnot only feature-preserving denoising for removing scanner noises, but also interactive detail editing for weakening or enhancing some specific geometric details.Various detail editing results are obtainedby reconstructingthe mesh fromnew processed differential edge coordinates, which are filtered from the view of signal processing, in linear least square sense.Experimental results and comparisonswith other methodsdemonstrate that our method is effective and robust.

Watertight surface reconstruction method for CAD models based on optimal transport

Feature-preserving mesh reconstruction from point clouds is challenging.Implicit methods tend to fit smooth surfaces and cannot be used to reconstruct sharp features.Explicit reconstruction methods are sensitive to noise and only interpolate sharp features when points are distributed on feature lines.We propose a watertight surface reconstruction method based on optimal transport that can accurately reconstruct sharp features often present in CAD models.We formalize the surface reconstruction problem by minimizing the optimal transport cost between the point cloud and the reconstructed surface.The algorithm consists of initialization and refinement steps.In the initialization step,the convex hull of the point cloud is deformed under the guidance of a transport plan to obtain an initial approximate surface.Next,the mesh surface was optimized using operations including vertex relocation and edge collapses/fips to obtain feature-preserving results.Experiments demonstrate that our method can preserve sharp features while being robust to noise and missing data.

Feature-Preserving Mesh Denoising via Anisotropic Surface Fitting

We propose in this paper a robust surface mesh denoising method that can effectively remove mesh noise while faithfully preserving sharp features. This method utilizes surface fitting and projection techniques. Sharp features are preserved in the surface fitting algorithm by considering an anisotropic neighborhood of each vertex detected by the normal-weighted distance. In addition, to handle the mesh with a high level of noise, we perform a pre-filtering of surface normals prior to the neighborhood searching. A number of experimental results and comparisons demonstrate the excellent performance of our method in preserving important surface geometries while filtering mesh noise.

Robust Mesh Smoothing

This paper proposes a vertex-estimation-based, feature-preserving smoothingtechnique for meshes. A robust mesh smoothing operator called mean value coordinates flow isintroduced to modify mean curvature flow and make it more stable. Also the paper proposes athree-pass vertex estimation based on bilateral filtering of local neighbors which is transferredfrom image processing settings and a Quasi-Laplacian operation, derived from the standard Laplacianoperator, is performed to increase the smoothness order of the mesh rapidly whilst denoising meshesefficiently, preventing volume shrinkage as well as preserving sharp features of the mesh. Comparedwith previous algorithms, the result shows it is simple, efficient and robust.

Least-squares images for edge-preserving smoothing

In this paper, we propose least-squares images(LS-images) as a basis for a novel edgepreserving image smoothing method. The LS-image requires the value of each pixel to be a convex linear combination of its neighbors, i.e., to have zero Laplacian, and to approximate the original image in a least-squares sense. The edge-preserving property inherits from the edge-aware weights for constructing the linear combination. Experimental results demonstrate that the proposed method achieves high quality results compared to previous state-of-theart works. We also show diverse applications of LSimages, such as detail manipulation, edge enhancement,and clip-art JPEG artifact removal.