在自然光旋转下实现高精度三维形状与反射率恢复
RotatedMVPS: Multi-view Photometric Stereo with Rotated Natural Light
- 利用旋转光源+多视角采集，降低自然光照复杂性
- 结合单视角学习先验，提升形状与反射率重建精度
- 适合真实场景逆渲染，无需暗室控制光照
多视角光度立体（MVPS）旨在从不同视角和光照下拍摄的图像中恢复高保真表面形状与反射特性。然而，现有方法通常依赖受控暗室环境进行光照变化，或忽略反射率与光照属性的恢复，限制了其在自然光照场景及下游逆渲染任务中的应用。本文提出RotatedMVPS，可在旋转自然光条件下实现形状与反射率恢复，仅需一个实用的旋转装置。通过确保不同相机与物体姿态下的光照一致性，显著减少复杂环境光带来的未知变量。此外，将现成的基于学习的单视角光度立体方法的数据先验融入MVPS框架，大幅提升了形状与反射率恢复的准确性。在合成与真实数据集上的实验结果验证了该方法的有效性。
原文摘要 · Abstract (English)
Multiview photometric stereo (MVPS) seeks to recover high-fidelity surface shapes and reflectances from images captured under varying views and illuminations. However, existing MVPS methods often require controlled darkroom settings for varying illuminations or overlook the recovery of reflectances and illuminations properties, limiting their applicability in natural illumination scenarios and downstream inverse rendering tasks. In this paper, we propose RotatedMVPS to solve shape and reflectance recovery under rotated natural light, achievable with a practical rotation stage. By ensuring light consistency across different camera and object poses, our method reduces the unknowns associated with complex environment light. Furthermore, we integrate data priors from off-the-shelf learning-based single-view photometric stereo methods into our MVPS framework, significantly enhancing the accuracy of shape and reflectance recovery. Experimental results on both synthetic and real-world datasets demonstrate the effectiveness of our approach.
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