Connect-and-Slice: An Hybrid Approach for Reconstructing 3D Objects
| Autor: | Hao Fang, Florent Lafarge |
|---|---|
| Přispěvatelé: | Geometric Modeling of 3D Environments (TITANE), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Lafarge, Florent |
| Rok vydání: | 2020 |
| Předmět: |
Laser scanning
Computer science business.industry Point cloud [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] 020207 software engineering 02 engineering and technology Iterative reconstruction [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] Robustness (computer science) Polygon 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Polygon mesh Computer vision Wafer Artificial intelligence business |
| Zdroj: | CVPR CVPR 2020-IEEE Conference on Computer Vision and Pattern Recognition CVPR 2020-IEEE Conference on Computer Vision and Pattern Recognition, Jun 2020, Seattle / Virtual, United States |
| Popis: | International audience; Converting point clouds generated by Laser scanning, multiview stereo imagery or depth cameras into compact polygon meshes is a challenging problem in vision. Existing methods are either robust to imperfect data or scalable, but rarely both. In this paper, we address this issue with an hybrid method that successively connects and slices planes detected from 3D data. The core idea consists in constructing an efficient and compact partitioning data structure. The later is i) spatially-adaptive in the sense that a plane slices a restricted number of relevant planes only, and ii) composed of components with different structural meaning resulting from a preliminary analysis of the plane connec-tivity. Our experiments on a variety of objects and sensors show the versatility of our approach as well as its competitiveness with respect to existing methods. |
| Databáze: | OpenAIRE |
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