Research on scene partition optimization and local adaptive rejection methods

Optimizing scene management and reducing rendering data are key to improving efficiency in the virtual real interaction of the metaverse. Using Morton codes to map three-dimensional spatial data into a linear number list, achieving reasonable partitioning of large-scale grids, and making improvements according to the needs of the metaverse. By using a hierarchical construction approach and utilizing the Morton code based BVH for coarse segmentation, combined with KD Tree for further segmentation, efficient scene partitioning is achieved. On this basis, focus on local adaptive removal of key areas to improve the running frame rate of digital twin scenes. Through this series of methods, unnecessary visibility analysis or deep query operations can be reduced while reducing scene state changes in each frame, thereby improving computer rendering efficiency and providing strong support for virtual real interaction in the metaverse.