Similar articles

Abstract: 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 stage, a novel salient measure deriving from the idea of neighbor supporting is developed. Benefiting from the integrated reliable salient measure feature, pseudo features can be effectively discriminated from the initially detected features and removed. Compared to previous methods based on the differential geometric property, the main advantage of our method is that it can detect both sharp and weak features. Numerical experiments show that our algorithm is robust, effective, and can produce more accurate results. We also discuss how detected features are incorporated into applications, such as feature-preserving mesh denoising and hole-filling, and present visually appealing results by integrating feature information.

[1]Bian, Z., Tong, R.F., 2011. Feature-preserving mesh denoising based on vertices classification. Comput. Aided Geom. Des., 28(1):50-64.

[2]Chen, C.Y., Cheng, K.Y., 2008. A sharpness-dependent filter for recovering sharp features in repaired 3D mesh models. IEEE Trans. Visual. Comput. Graph., 14(1):200-212.

[3]Demarsin, K., Vanderstraeten, D., Volodine, T., Roose, D., 2007. Detection of closed sharp edges in point clouds using normal estimation and graph theory. Comput.-Aided Des., 39(4):276-283.

[4]di Angelo, L., di Stefano, P., 2010. C¹ continuities detection in triangular meshes. Comput.-Aided Des., 42(9):828-839.

[5]Fan, H.Q., Yu, Y.Z., Peng, Q.S., 2010. Robust feature-preserving mesh denoising based on consistent subneighborhoods. IEEE Trans. Visual. Comput. Graph., 16(2):312-324.

[6]Fleishman, S., Drori, I., Cohen-Or, D., 2003. Bilateral Mesh Denoising. SIGGRAPH, p.950-953.

[7]Hildebrandt, K., Polthier, K., Wardetzky, M., 2005. Smooth Feature Lines on Surface Meshes. Proc. 3rd Eurographics Symp. Geometry Processing, p.85-90.

[8]Hubeli, A., Gross, M., 2001. Multiresolution Feature Extraction for Unstructured Meshes. Proc. Conf. on Visualization, p.287-294.

[9]Kim, H.S., Choi, H.K., Lee, K.H., 2009. Feature detection of triangular meshes based on tensor voting theory. Comput.-Aided Des., 41(1):47-58.

[10]Kim, S.K., Kim, C.H., 2006. Finding ridges and valleys in a discrete surface using a modified MLS approximation. Comput.-Aided Des., 38(2):173-180.

[11]Kim, S.K., Kim, S.J., Kim, C.H., 2006. Extraction of ridges-valleys for feature-preserving simplification of polygonal models. LNCS, 3992:279-286.

[12]Lai, Y.K., Zhou, Q.Y., Hu, S.M., Wallner, J., Pottmann, H., 2007. Robust feature classification and editing. IEEE Trans. Visual. Comput. Graph., 13(1):34-45.

[13]Lee, C.H., Varshney, A., Jacobs, D.W., 2005. Mesh Saliency. SIGGRAPH, p.659-666.

[14]Li, Z., Meek, D.S., Walton, D.J., 2010. Polynomial blending in a mesh hole-filling application. Comput.-Aided Des., 42(4):340-349.

[15]Liu, Y.S., Liu, M., Kihara, D., Ramani, K., 2007. Salient Critical Points for Meshes. Proc. ACM Symp. on Solid and Physical Modeling, p.277-282.

[16]Mao, Z.H., Cao, G., Zhao, M.X., 2009. Robust detection of perceptually salient features on 3D meshes. Vis. Comput., 25(3):289-295.

[17]Moreno, R., Garcia, M.A., Puig, D., Pizarro, L., Burgeth, B., Weickert, J., 2011. On improving the efficiency of tensor voting. IEEE Trans. Pattern Anal. Mach. Intell., 33(11):2215-2228.

[18]Ohtake, Y., Belyaev, A., Seidel, H.P., 2004. Ridge-valley lines on meshes via implicit surface fitting. ACM Trans. Graph., 23(3):609-612.

[19]Page, D.L., Sun, Y., Koschan, A.F., Paik, J., Abidi, M.A., 2002. Normal vector voting: crease detection and curvature estimation on large, noisy meshes. Graph. Models, 64(3-4):199-229.

[20]Sahner, J., Weber, B., Prohaska, S., Lamecker, H., 2008. Extraction of feature lines on surface meshes based on discrete Morse theory. Comput. Graph. Forum, 27(3):735-742.

[21]Shimizu, T., Date, H., Kanai, S., Kishinami, T., 2005. A New Bilateral Mesh Smoothing Method by Recognizing Features. 9th Int. Conf. on Computer Aided Design and Computer Graphics, p.281-286.

[22]Stylianou, G., Farin, G., 2004. Crest lines for surface segmentation and flattening. IEEE Trans. Visual. Comput. Graph., 10(5):536-544.

[23]Su, Z.X., Wang, H., Cao, J.J., 2009. Mesh Denoising Based on Differential Coordinates. IEEE Int. Conf. on Shape Modeling and Applications, p.1-6.

[24]Sunil, V.B., Pande, S.S., 2008. Automatic recognition of features from freeform surface CAD models. Comput.-Aided Des., 40(4):502-517.

[25]Taubin, G., 1995. Estimating the Tensor of Curvature of a Surface from a Polyhedral Approximation. 5th Int. Conf. on Computer Vision, p.902-907.

[26]Wang, C.C.L., 2006a. Bilateral recovering of sharp edges on feature-insensitive sampled meshes. IEEE Trans. Visual. Comput. Graph., 12(4):629-639.

[27]Wang, C.C.L., 2006b. Incremental reconstruction of sharp edges on mesh surfaces. Comput.-Aided Des., 38(6):689-702.

[28]Wang, H., Chen, H.Y., Su, Z.X., Cao, J.J., Liu, F.S., Shi, X.Q., 2011. Versatile surface detail editing via Laplacian coordinates. Vis. Comput., 27(5):401-411.

[29]Wang, S.F., Hou, T.B., Su, Z.X., Qin, H., 2011. Diffusion Tensor Weighted Harmonic Fields for Feature Classification. PG, p.93-98.

[30]Wang, X.C., Liu, X.P., Lu, L.F., Li, B.J., Cao, J.J., Yin, B.C., Shi, X.Q., 2012. Automatic hole-filling of CAD model with feature-preserving. Comput. Graph., 36(2):101-110.

[31]Watanabe, K., Belyaev, A.G., 2001. Detection of salient curvature features on polygonal surfaces. Comput. Graph. Forum, 20(3):385-392.

[32]Weinkauf, T., Günther, D., 2009. Separatrix persistence: extraction of salient edges on surfaces using topological methods. Comput. Graph. Forum, 28(5):1519-1528.

[33]Yang, Y.L., Lai, Y.K., Hu, S.M., Pottmann, H., 2006. Robust Principal Curvatures on Multiple Scales. Proc. 4th Eurographics Symp. on Geometry Processing, p.223-226.

[34]Yoshizawa, S., Belyaev, A., Seidel, H.P., 2005. Fast and Robust Detection of Crest Lines on Meshes. Proc. ACM Symp. on Solid and Physical Modeling, p.227-232.

[35]Yoshizawa, S., Belyaev, A., Yokota, H., Seidel, H.P., 2008. Fast, robust, and faithful methods for detecting crest lines on meshes. Comput. Aided Geom. Des., 25(8):545-560.