面向可扩展的几何和材料多视图重建
IEEE transactions on pattern analysis and machine intelligence
|September 14, 2023
概括
本研究介绍了一种可扩展的方法,用于从手持式扫描仪重建3D场景,从而能够准确地估计相机姿势,几何形状和空间变化的双向反射分布函数 (svBRDF). 该方法确保从大型数据集中获得全球一致的模型.
科学领域:
- 计算机视觉 计算机视觉
- 计算机图形 计算机图形
- 三维重建的3D重建
背景情况:
- 从捕获的数据中估计3D场景属性,如几何和材料,对于各种应用至关重要.
- 现有的方法很难处理大规模的场景,或者需要专门的,静止的捕捉设置.
- 移动捕获系统提供了灵活性,但在数据处理和重建准确性方面存在挑战.
研究的目的:
- 开发一种新的,可扩展的方法来共同恢复相机姿势,物体几何和空间变化的双向反射分布函数 (svBRDF).
- 为了使超越物体尺寸的3D场景能够使用移动,手持捕捉系统进行重建.
- 为准确和全球一致的3D场景建模提供统一的框架.
主要方法:
- 使用来自移动手持系统的高分辨率RGB-D图像,具有主动点灯照明.
- 在一个单一的客观函数中制定联合估计问题,通过基于梯度的解法器最小化.
- 实施分布式优化算法,用于重建基于2.5D关键的场景表示.
- 引入多视图一致性调节器,以便将本地优化无集成到全球模型中.
主要成果:
- 与现有的基线方法相比,证明了有利的比较.
- 成功地重建了各种各样的物体和材料,准确度很高.
- 展示了该方法对于空间较大的场景和大量观察视图的可扩展性.
- 在拟议的配方中验证了单个成分的重要性.
结论:
- 拟议的方法在可扩展的几何学和从手持式扫描仪的材料估计方面取得了重大进展.
- 该方法可以从复杂的大型场景中创建全球一致的3D模型.
- 这项工作为使用移动捕获技术更容易访问和更准确的3D内容创建铺平了道路.
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