Segmentation-driven feature-preserving mesh denoising
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s00371-023-03161-w.pdf
Reference57 articles.
1. Ströter, D., Mueller-Roemer, J.S., Weber, D., Fellner, D.W.: Fast harmonic tetrahedral mesh optimization. Vis. Comput. 38(9), 3419–3433 (2022). https://doi.org/10.1007/s00371-022-02547-6
2. Jia, S., Zhang, W., Wang, G., Pan, Z., Yu, X.: A real-time deformable cutting method using two levels of linked voxels for improved decoupling between collision and rendering. Vis. Comput. 39(2), 765–783 (2022). https://doi.org/10.1007/s00371-021-02373-2
3. Prashant, G.: A survey of modeling, rendering and animation of clouds in computer graphics. Vis. Comput. 37(7), 1931–1948 (2020). https://doi.org/10.1007/s00371-020-01953-y
4. Sun, X., Rosin, P.L., Martin, R., Langbein, F.: Fast and effective feature-preserving mesh denoising. IEEE Trans. Vis. Comput. Graph. 13(5), 925–938 (2007)
5. Zheng, Y., Fu, H., Au, O.K.C., Tai, C.L.: Bilateral normal filtering for mesh denoising. IEEE Trans. Vis. Comput. Graph. 17(10), 1521–1530 (2011)
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