概括
本研究介绍了一种快速的隐性射线雕刻方法,使用层次神经辐射场 (NeRF) 来从影子图像中重建隐藏的物体. 它显著降低了计算延迟,以实现高效的3D场景重建.
科学领域:
- 计算机视觉 计算机视觉
- 计算成像技术的成像
- 三维重建的3D重建
背景情况:
- 两弹非视线 (NLoS) 成像提供了使用反射激光光的隐藏物体的低成本重建.
- 由于详细隐藏目标描绘所需的射线数量多,现有的方法在计算延迟方面遇到了困难.
研究的目的:
- 开发一种快速有效的方法来使用隐式方法重建隐藏对象.
- 为了减少NLoS成像中的计算延迟,同时保持高保真度的3D重建.
主要方法:
- 一个层次的神经辐射场 (NeRF) 模型用于隐性3D重建.
- 多视图影子图像被空间和时间分解,以提取必要的光线.
- 使用这些关键射线优化了NeRF模型,减少了冗余,以实现高效的重建.
主要成果:
- 拟议的方法实现了对静态和动态封闭场景的有效隐藏对象重建.
- 在20m×10m×4m体积内显示出2%的相对深度偏差.
- 成功地分辨出精细目标,横向分辨率高达6厘米,轴向分辨率高达3厘米.
结论:
- 使用层级NeRF的隐性射线雕刻方法为NLoS 3D重建提供了准确且计算效率高的解决方案.
- 这种方法显著克服了以前明确方法的延迟限制.
- 能够在复杂的,封闭的环境中对隐藏物体进行高分辨率的成像.
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