拓扑(电路)
几何学
计算机科学
几何和拓扑
数学
组合数学
摘要
This paper presents a methodology for correcting geometric and topological errors, specifically addressing fragmented and disconnected components in buildings (FDCB) in 3D models intended for urban digital twin (UDT). The proposed two-stage approach combines geometric refinement via duplicate vertex removal with topological refinement using a novel spatial partitioning-based Depth-First Search (DFS) algorithm for connected mesh clustering. This spatial partitioning-based DFS significantly improves upon traditional graph traversal methods like standard DFS, breadth-first search (BFS), and Union-Find for connectivity analysis. Experimental results demonstrate that the spatial DFS algorithm significantly improves computational speed, achieving processing times approximately seven times faster than standard DFS and 17 times faster than BFS. In addition, the proposed approach achieves a data size ratio of approximately 20% in the simplified mesh, compared to the 50–60% ratios typically observed with established techniques like Quadric Decimation and Vertex Clustering. This research enhances the quality and usability of 3D building models with FDCB issues for UDT applications.
科研通智能强力驱动
Strongly Powered by AbleSci AI