单张图像实现近光非朗伯表面的高精度三维重建
Near-Light Color Photometric Stereo for Mono-Chromatic Non-Lambertian Surfaces
- 用神经隐式表示同时建模深度与反射率，解决单图重建难题
- 在近光和非朗伯条件下仍能实现高精度表面恢复
- 适用于真实场景下的快速三维扫描，适合工业检测应用
彩色光照立体技术可实现单次拍摄下的表面重建，突破了传统光照立体需多图、静态场景下变光的限制，拓展至动态场景。然而，现有方法大多假设理想远距离光源和朗伯反射模型，对更实际的近光条件和非朗伯表面研究不足。为此，本文提出一种基于神经隐式表示的框架，在单色性（均匀色度与同质材质）假设下，联合建模深度与双向反射分布函数（BRDF），缓解彩色光照立体固有的病态问题，仅凭一张图像即可实现精细表面重建。此外，设计了一款紧凑型光学触觉传感器用于验证。在合成与真实数据集上的实验表明，该方法具备准确性和鲁棒性。
原文摘要 · Abstract (English)
Color photometric stereo enables single-shot surface reconstruction, extending conventional photometric stereo that requires multiple images of a static scene under varying illumination to dynamic scenarios. However, most existing approaches assume ideal distant lighting and Lambertian reflectance, leaving more practical near-light conditions and non-Lambertian surfaces underexplored. To overcome this limitation, we propose a framework that leverages neural implicit representations for depth and BRDF modeling under the assumption of mono-chromaticity (uniform chromaticity and homogeneous material), which alleviates the inherent ill-posedness of color photometric stereo and allows for detailed surface recovery from just one image. Furthermore, we design a compact optical tactile sensor to validate our approach. Experiments on both synthetic and real-world datasets demonstrate that our method achieves accurate and robust surface reconstruction.
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