Camera Path Generation for Triangular Mesh Using Toroidal Patches
Source abstract
Abstract
Triangular mesh data structures are principal in computer graphics, serving as the foundation for many 3D models. To effectively utilize these 3D models across diverse industries, it is important to understand the model’s overall shape and geometric features thoroughly. In this work, we introduce a novel method for generating camera paths that emphasize the model’s local geometric characteristics. This method uses a toroidal patch-based spatial data structure, approximating the mesh’s faces within a predetermined tolerance ϵ, encapsulating their geometric intricacies. This facilitates the determination of the camera position and gaze path, ensuring the mesh’s key characteristics are captured. During the path construction, we create a bounding cylinder for the mesh, project the mesh’s faces and associated toroidal patches onto the cylinder’s lateral surface, and sequentially select grids of the cylinder containing the highest number of toroidal patches as we traverse the lateral surface. The centers of the selected grids are used as control points for a periodic B-spline curve, which serves as our foundational path. After initial curve generation, we generated camera position and gaze path from the curve by multiplying factors to ensure a uniform camera amplitude. We applied our method to ten triangular mesh models, demonstrating its effectiveness and adaptability across various mesh configurations.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: 3D Shape Modeling and Analysis · Computer Graphics and Visualization Techniques · Computational Geometry and Mesh Generation
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Computer Engineering, Dong-A University, Busan 49315, Republic of Korea
Funding
National Research Foundation of Korea · Institute for Information & communications Technology Promotion
References (31)
Show source-provided references
1. Zhao, F., and Sun, G. (2023). Planar Delaunay Mesh Smoothing Method Based on Angle and a Deep Q-Network. Appl. Sci., 13.10.3390/app13169157 ↗
2. Park, J.H., Moon, J.H., Park, S., and Yoon, S.H. (2022). GeoStamp: Detail Transfer Based on Mean Curvature Field. Mathematics, 10.10.3390/math10030500 ↗
3. Gao, M., Ruan, N., Shi, J., and Zhou, W. (2022). Deep Neural Network for 3D Shape Classification Based on Mesh Feature. Sensors, 22.10.3390/s22187040 ↗
4. Ha, Y., Park, J.H., and Yoon, S.H. (2021). Geodesic Hermite Spline Curve on Triangular Meshes. Symmetry, 13.10.3390/sym13101936 ↗
5. Vázquez, P.P., Feixas, M., Sbert, M., and Heidrich, W. (2001, January 21–23). Viewpoint selection using viewpoint entropy. Proceedings of the VMV, Citeseer, Stuttgart, Germany.
6. Habibi, Z., Caron, G., and Mouaddib, E.M. (2014, January 1–2). 3d model automatic exploration: Smooth and intelligent virtual camera control. Proceedings of the Computer Vision—ACCV 2014 Workshops, Singapore.10.1007/978-3-319-16631-5_45 ↗
7. Saleem, W., Song, W., Belyaev, A., and Seidel, H.P. (2007, January 26–28). On computing best fly. Proceedings of the 23rd Spring Conference on Computer Graphics, Budmerice, Slovakia.10.1145/2614348.2614365 ↗
8. Han, S.R., Yamasaki, T., and Aizawa, K. (2010, January 26–29). Automatic preview video generation for mesh sequences. Proceedings of the 2010 IEEE International Conference on Image Processing, Hong Kong, China.10.1109/ICIP.2010.5652185 ↗
9. Li, Y., Cui, Q., Dou, F., Zhang, L., and Zhou, Z. (2014, January 14–18). Automatic mesh animation preview. Proceedings of the 2014 IEEE International Conference on Multimedia and Expo (ICME), Chengdu, China.10.1109/ICME.2014.6890271 ↗
10. Automatic Mesh Animation Preview with User Voting-Based Refinement10.1109/TMM.2016.2612124 ↗
11. Zhao, S., Ooi, W.T., Carlier, A., Morin, G., and Charvillat, V. (March, January 26). 3D mesh preview streaming. Proceedings of the 4th ACM Multimedia Systems Conference, Oslo, Norway.
12. Bandwidth adaptation for 3D mesh preview streaming10.1145/2537854 ↗
13. Oskam, T., Sumner, R.W., Thuerey, N., and Gross, M. (2009, January 1–2). Visibility transition planning for dynamic camera control. Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, New Orleans, LA, USA.10.1145/1599470.1599478 ↗
14. Amamra, A., Amara, Y., Benaissa, R., and Merabti, B. (2016, January 13–15). Optimal camera path planning for 3D visualisation. Proceedings of the 2016 SAI Computing Conference (SAI), London, UK.10.1109/SAI.2016.7556011 ↗
15. A novel cubic-order algorithm for approximating principal direction vectors10.1145/966131.966134 ↗
16. A New Spatial Data Structure for Triangular Mesh with Toroidal Patches
17. The Variables of Surface of Revolution and its effects on Human Visual Preference10.15701/kcgs.2022.28.4.31 ↗
18. Taubin, G. (1995, January 20–23). Estimating the tensor of curvature of a surface from a polyhedral approximation. Proceedings of the IEEE International Conference on Computer Vision, Cambridge, MA, USA.
19. Meyer, M., Desbrun, M., Schröder, P., and Barr, A.H. (2003, January 22–25). Discrete differential-geometry operators for triangulated 2-manifolds. Proceedings of the Visualization and Mathematics III, Berlin, Germany.10.1007/978-3-662-05105-4_2 ↗
20. Kalogerakis, E., Simari, P., Nowrouzezahrai, D., and Singh, K. (2007, January 4–6). Robust statistical estimation of curvature on discretized surfaces. Proceedings of the Symposium on Geometry Processing, Barcelona, Spain.
21. Curvature estimation for meshes based on vertex normal triangles10.1016/j.cad.2011.06.006 ↗
22. Estimation of differential quantities using Hermite RBF interpolation10.1007/s00371-017-1438-x ↗
23. Desbrun, M., Meyer, M., Schröder, P., and Barr, A.H. (1999, January 8–13). Implicit fairing of irregular meshes using diffusion and curvature flow. Proceedings of the 26th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH’99, Los Angeles, CA, USA.10.1145/311535.311576 ↗
24. Optimizing 3D triangulations using discrete curvature analysis
25. Kim, S.J., Kim, S.K., and Kim, C.H. (2002, January 9–11). Discrete differential error metric for surface simplification. Proceedings of the 10th Pacific Conference on Computer Graphics and Applications, Beijing, China.
26. Surface simplification using a discrete curvature norm10.1016/S0097-8493(02)00121-8 ↗
27. Triangular surface mesh fairing via Gaussian curvature flow10.1016/j.cam.2005.03.094 ↗
28. Surface–surface-intersection computation using a bounding volume hierarchy with osculating toroidal patches in the leaf nodes10.1016/j.cad.2020.102866 ↗
29. Self-intersection computation for freeform surfaces based on a regional representation scheme for miter points10.1016/j.cagd.2021.101979 ↗
30. Precise Hausdorff distance computation for freeform surfaces based on computations with osculating toroidal patches10.1016/j.cagd.2021.101967 ↗
31. Botsch, M., Kobbelt, L., Pauly, M., Alliez, P., and Lévy, B. (2010). Polygon Mesh Processing, CRC Press.10.1201/b10688 ↗