Surface remeshing is widely used in computer vision and reverse engineering. The vertex normal vectors used in the existing surface remeshing methods are not accurate enough in the characteristic regions such as large curvature change, boundary and sharp edge, which leads to poor remeshing results in these regions. In this paper, the vertex normal vector based on hybrid weight and boundary correction is introduced to our method. We use this normal vector to improve the reprojection step in vertex translation, and combining edge splitting, collapsing, and flipping, propose an improved real-time adaptive remeshing method. Three models are selected for remeshing experiments. Compared with the RAR (real-time adaptive remeshing) method based on Thürrner's vertex normal, the Hausdorff distance is reduced by 4.99%, 8.79% and 6.85% respectively in the uniform length remeshing, and 3.21%, 2.25% and 11.92% respectively in the adaptive length remeshing. The results show that the remeshing effect obtained by our method is smoother and has higher geometric similarity with the original model.
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