完全自动化的结构光扫描,通过图形优化实现高准确度的3D重建
Optics express
|April 4, 2024
概括
本研究介绍了一种用于高保真度3D重建的新型图形优化方法,在大规模建模中显著减少错误和手工劳动. 这种方法确保了工业应用的无,准确的3D模型.
科学领域:
- 计算机视觉 计算机视觉
- 几何建模 几何建模
- 三维重建的3D重建
背景情况:
- 当前的3D扫描方法面临着高人工成本和大规模项目的错误积累的挑战.
- 实现工业级,无,高保真度的3D模型与最小的手动干预仍然是一个重大挑战.
研究的目的:
- 开发一种创新的工业级无和高保真3D重建方法,使用最小的手工干预.
- 为了解决多记录中的错误积累,并提高表面模型质量.
主要方法:
- 将多注册转换为图形优化问题,使用点云跨多路径注册实现全球一致性.
- 采用基于几何和颜色差异的动态非线性权重,优化使用代重量最小方程 (IRLS) 进行捆绑调整 (BA).
- 引入了多融合的本地到全球过渡战略,以确保防水,无表面模型和正确的正常向量一致性.
主要成果:
- 与传统的框架对框架方法相比,显著提高了注册准确性和稳定性.
- 在实现近实时效率的同时,在3D重建中保持高保真度.
- 成功生成了防水和无表面模型,有效地纠正了网格不连续性.
结论:
- 拟议的图形优化和多融合策略为工业级3D重建提供了强大而高效的解决方案.
- 该方法在准确性,强度和无表面生成方面表现出卓越的性能.
- 开源数据和实施鼓励社区进一步开发3D重建技术.
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