Abstract
The extraction of 3D models represented by Constructive Solid Geometry (CSG) trees from point clouds is a common problem in reverse engineering pipelines as used by Computer Aided Design (CAD) tools. We propose three independent enhancements on state-of-the-art Genetic Algorithms (GAs) for CSG tree extraction: (1) A deterministic point cloud filtering mechanism that significantly reduces the computational effort of objective function evaluations without loss of geometric precision, (2) a graph-based partitioning scheme that divides the problem domain in smaller parts that can be solved separately and thus in parallel and (3) a 2-level improvement procedure that combines a recursive CSG tree redundancy removal technique with a local search heuristic, which significantly improves GA running times. We show in an extensive evaluation that our optimized GA-based approach provides faster running times and scales better with problem size compared to state-of-the-art GA-based approaches.
| Item Type: | Journal article |
|---|---|
| Faculties: | Mathematics, Computer Science and Statistics > Computer Science |
| Subjects: | 000 Computer science, information and general works > 004 Data processing computer science |
| Language: | English |
| Item ID: | 82254 |
| Date Deposited: | 15. Dec 2021, 15:01 |
| Last Modified: | 15. Dec 2021, 15:01 |
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