Optimizations for Hierarchical Levels of Detail Generation on Large-Scale Polygonal Scenes

Alternative levels of detail (LOD) are one of the most promising approaches to effective rendering of complex spatial 3D scenes. The approach has been realized in the hierarchical levels of detail (HLOD) and hierarchical dynamic levels of detail (HDLOD) methods, which are currently well studied and successfully applied for conservative and interactive rendering of large dynamic scenes. At the same time, the issues of efficient generation of levels of detail, which are critical in a number of applications related to visual modeling of complex industrial projects and large-scale infrastructure programs, have not received due attention. The paper considers emerging techniques for accelerating HLOD and HDLOD generation. It also discusses the possibility of quickly updating hierarchical levels of detail, taking into account permanent local changes in the three-dimensional model, typical for collaborative applications.

1. Clark J. H. Hierarchical geometric models for visible surface algorithms. Communications of the ACM. – 1976. – Т. 19. – №. 10. – С. 547-554.

2. Rossignac J., Borrel P. Multi-resolution 3D approximations for rendering complex scenes. Modeling in computer graphics: methods and applications. – Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. – С. 455-465.

3. Heckbert P., Garland M. Multiresolution modeling for fast rendering. Graphics Interface. – Canadian Information Processing Society, 1994. – С. 43-43.

4. Erikson C., Manocha D., Baxter III W. V. HLODs for faster display of large static and dynamic environments. Proceedings of the 2001 symposium on Interactive 3D graphics. – 2001. – С. 111-120.

5. Varadhan G., Manocha D. Out-of-core rendering of massive geometric environments. IEEE Visualization, 2002. VIS 2002. – IEEE, 2002. – С. 69-76.

6. Lakhia A. Efficient interactive rendering of detailed models with hierarchical levels of detail. Proceedings. 2nd International Symposium on 3D Data Processing, Visualization and Transmission, 2004. 3DPVT 2004. – IEEE, 2004. – С. 275-282.

7. Семёнов В.А., Шуткин В.Н., Золотов В.А., Морозов С.В. Расширение метода иерархических уровней детализации для динамических сцен с детерминированным характером событий. Труды конференции ГрафиКон-2019, стр. 37-41, DOI: 10.30987/graphicon-2019-1-37-41.

8. Semenov V.A., Shutkin V.N., Zolotov V.A., Morozov S.V., Gonakhchyan V.I. Visualization of Large Scenes with Deterministic Dynamics. Programming and Computer Software, 2020, 46(3), pp. 223–232.

9. V. Semenov, V. Shutkin, V. Zolotov. Conservative Out-of-Core Rendering of Large Dynamic Scenes Using HDLODs. Proceedings of the 31st International Conference on Computer Graphics and Vision (GraphiCon 2021), 2021, Nizhny Novgorod, Russia, pp. 105-115, DOI:10.20948/graphicon-2021-3027-105-115.

10. Shutkin V., Semenov V., Zolotov V., Morozkin N. Alternative HDLOD method for large scenes with multiple dynamic behaviors. Proceedings of 17th International Conference on Computer Graphics, Visualization, Computer Vision and Image Processing, Porto, Portugal 16 – 18 July 2023, pp. 141-148.

11. Garland M., Heckbert P. S. Surface simplification using quadric error metrics. Proceedings of the 24th annual conference on Computer graphics and interactive techniques. – 1997. – С. 209-216.

12. Schroeder W. J., Zarge J. A., Lorensen W. E. Decimation of triangle meshes. Proceedings of the 19th annual conference on Computer graphics and interactive techniques. – 1992. – С. 65-70.

13. Low K. L., Tan T. S. Model simplification using vertex-clustering. Proceedings of the 1997 symposium on Interactive 3D graphics. – 1997. – С. 75-ff.

14. Luebke D. et al. Level of detail for 3D graphics. – Elsevier, 2002.

15. Michaud C., Mellado N., Paulin M. Mesh simplification with curvature error metric. Eurographics 2017. – 2017.

16. Liang Y., He F., Zeng X. 3D mesh simplification with feature preservation based on whale optimization algorithm and differential evolution. Integrated Computer-Aided Engineering. – 2020. – Т. 27. – №. 4. – С. 417-435.

17. Hasselgren J. et al. Appearance-Driven Automatic 3D Model Simplification. EGSR (DL). – 2021. – С. 85 -97.

18. Lindstrom P., Turk G. Image-driven simplification. ACM Transactions on Graphics (ToG). – 2000. – Т. 19. – №. 3. – С. 204-241.

19. Zhou Z., Chen K., Zhang J. Efficient 3-D scene prefetching from learning user access patterns. IEEE Transactions on Multimedia. – 2015. – Т. 17. – №. 7. – С. 1081-1095.

20. Chen J. et al. Optimally redundant, seek-time minimizing data layout for interactive rendering. The Visual Computer. – 2017. – Т. 33. – С. 139-149.

21. Peng C., Cao Y. A GPU‐based approach for massive model rendering with frame‐to‐frame coherence. Computer Graphics Forum. – Oxford, UK : Blackwell Publishing Ltd, 2012. – Т. 31. – №. 2pt2. – С. 393- 402.

22. Peng C., Cao Y. Parallel LOD for CAD model rendering with effective GPU memory usage. Computer-Aided Design and Applications. – 2016. – Т. 13. – №. 2. – С. 173-183.

23. Zhao T., Jiang J., Guo X. A Novel Quadratic Error Metric Mesh Simplification Algorithm For 3D Building Models Based On ‘Local-Vertex’ Texture Featues. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. – 2022. – Т. 48. – С. 109-115.

24. Salinas D., Lafarge F., Alliez P. Structure‐aware mesh decimation. Computer Graphics Forum. – 2015. – Т. 34. – №. 6. – С. 211-227.

25. Li M., Nan L. Feature-preserving 3D mesh simplification for urban buildings. ISPRS Journal of Photogrammetry and Remote Sensing. – 2021. – Т. 173. – С. 135-150.

26. Ge Y. et al. A Novel LOD Rendering Method with Multi-level Structure Keeping Mesh Simplification and Fast Texture Alignment for Realistic 3D Models. IEEE Transactions on Geoscience and Remote Sensing. – 2024.

27. Zhou S. et al. A hybrid level‐of‐detail representation for large‐scale urban scenes rendering. Computer Animation and Virtual Worlds. – 2014. – Т. 25. – №. 3-4. – С. 243-253.

28. Zhang L. et al. Web-based visualization of large 3D urban building models. International Journal of Digital Earth. – 2014. – Т. 7. – №. 1. – С. 53-67.

29. Liang J. et al. InfNeRF: Towards Infinite Scale NeRF Rendering with O (log n) Space Complexity. SIGGRAPH Asia 2024 Conference Papers. – 2024. – С. 1-11.

30. Kerbl B. et al. A hierarchical 3d gaussian representation for real-time rendering of very large datasets. ACM Transactions on Graphics (TOG). – 2024. – Т. 43. – №. 4. – С. 1-15.

31. Pečnik S., Žalik B. Real-time visualization using GPU-accelerated filtering of lidar data. World Acad. Sci., Eng. Technol., Int. J. Comput., Elect., Automat., Control Inf. Eng. – 2014. – Т. 8. – №. 12. – С. 2108- 2112.

32. Zhou Y. et al. Efficient Scene Appearance Aggregation for Level-of-Detail Rendering. arXiv preprint arXiv:2409.03761. – 2024.

33. Loubet G., Neyret F. Hybrid mesh‐volume LoDs for all‐scale pre‐filtering of complex 3D assets. Computer Graphics Forum. – 2017. – Т. 36. – №. 2. – С. 431-442.