通过稀疏到密集的立体声匹配和基于斜线函数的抛物线建模进行强大的单一拍摄3D重建
概括
本研究引入了一种新的稀密结构光 (SL) 方法,用于主动立体视觉 (ASV),以实现高分辨率的3D表面成像. 该方法可强大重建复杂的3D形状,并提高精度.
科学领域:
- 计算机视觉 计算机视觉
- 3D成像是3D成像中的一种.
- 光学计量学 在光学计量学
背景情况:
- 高精度,高分辨率的3D表面成像对于学术和工业应用至关重要.
- 现有的主动立体视觉 (ASV) 方法在稳固重建复杂的3D形状方面面临挑战.
研究的目的:
- 开发一种基于线条图案的新型稀密结构光 (SL) ASV方法.
- 为了实现强大且高分辨率的3D形状重建.
主要方法:
- 提出了一种稀疏至密集的立体声匹配 (SDSM) 方法用于线路集群和匹配.
- 设计了一个四色SL线条图案,线条密度不同.
- 开发了一个基于spline函数的抛物模型 (SFPM) 用于深度计算.
主要成果:
- 在SDSM方法有效集群和匹配稀疏和密集的色线.
- 该SFPM准确计算匹配的颜色线之间的深度.
- 实验结果表明,与现有方法相比,其强度更高,特别是对于复杂的形状.
结论:
- 拟议的SDSM-SFPM ASV方法为高分辨率的3D表面成像提供了一个强大的解决方案.
- 这种技术显著改善了复杂的3D几何结构的重建.
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