IEEE Trans Image Process. 2017 Mar;26(3):1089-1101. doi: 10.1109/TIP.2016.2636661. Epub 2016 Dec 7.
We propose a novel framework for photometric stereo (PS) under low-light conditions using uncalibrated near-light illumination. It operates on free-form video sequences captured with a minimalistic and affordable setup. We address issues such as albedo variations, shadowing, perspective projections, and camera noise. Our method uses specular spheres detected with a perspective-correcting Hough transform to robustly triangulate light positions in the presence of outliers via a least-squares approach. Furthermore, we propose an iterative reweighting scheme in combination with an ℓ-norm minimizer to robustly solve the calibrated near-light PS problem. In contrast to other approaches, our framework reconstructs depth, albedo (relative to light source intensity), and normals simultaneously and is demonstrated on synthetic and real-world scenes.
我们提出了一种新的基于非标定近光照明的低光照光度立体视觉（PS）框架。它可以在使用极简和经济实惠的设置拍摄的自由格式视频序列上运行。我们解决了反射率变化、阴影、透视投影和相机噪声等问题。我们的方法使用通过透视校正的霍夫变换检测到的镜面球，通过最小二乘方法在存在离群点的情况下稳健地三角化光线位置。此外，我们提出了一种迭代加权方案，并结合 ℓ-norm 最小化器来稳健地解决标定近光 PS 问题。与其他方法相比，我们的框架可以同时重建深度、反射率（相对于光源强度）和法向，并在合成和真实场景中进行了演示。
