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In this paper, we propose an automatic hole-filling method, particularly for recovering missing feature curves and corners. We first extract the feature vertices around a hole of a CAD model and classify them into different feature sets. These feature sets are then automatically paired, using ordered double normals, Gaussian mapping and convex/concave(More)
In this paper, we present a robust normal estimation algorithm based on the low-rank subspace clustering technique. The main idea is based on the observation that compared with the points around sharp features, it is relatively easier to obtain accurate normals for the points within smooth regions. The points around sharp features and smooth regions are(More)
Consistent normal orientation is challenging in the presence of noise, non-uniformities and thin sharp features. None of any existing local or global methods is capable of orienting all point cloud models consistently, and none of them offers a mechanism to rectify the inconsistent normals. In this paper, we present a new normal orientation method based on(More)
We propose a robust method for detecting features on triangular meshes by combining normal tensor voting with neighbor supporting. Our method contains two stages: feature detection and feature refinement. First, the normal tensor voting method is modified to detect the initial features, which may include some pseudo features. Then, at the feature refinement(More)