Li Boren, Furukawa Tomonari
Beijing Institute for General Artificial Intelligence, Beijing 100124, China.
School of Engineering and Applied Science, University of Virginia, Charlottesville, VA 22904, USA.
J Imaging. 2022 Feb 8;8(2):40. doi: 10.3390/jimaging8020040.
This paper presents a photometric stereo (PS) method based on the dichromatic reflectance model (DRM) using colour images. The proposed method estimates surface orientations for surfaces with non-Lambertian reflectance using diffuse-specular separation and contains two steps. The first step, referred to as diffuse-specular separation, initialises surface orientations in a specular invariant colour subspace and further separates the diffuse and specular components in the RGB space. In the second step, the surface orientations are refined by first initialising specular parameters via solving a log-linear regression problem owing to the separation and then fitting the DRM using Levenburg-Marquardt algorithm. Since reliable information from diffuse reflection free from specularities is adopted in the initialisations, the proposed method is robust and feasible with less observations. At pixels where dense non-Lambertian reflectances appear, signals from specularities are exploited to refine the surface orientations and the additionally acquired specular parameters are potentially valuable for more applications, such as digital relighting. The effectiveness of the newly proposed surface normal refinement step was evaluated and the accuracy in estimating surface orientations was enhanced around 30% on average by including this step. The proposed method was also proven effective in an experiment using synthetic input images comprised of twenty-four different reflectances of dielectric materals. A comparison with nine other PS methods on five representative datasets further prove the validity of the proposed method.
本文提出了一种基于二向色反射模型（DRM）的光度立体（PS）方法，该方法使用彩色图像。所提出的方法通过漫反射-镜面反射分离来估计具有非朗伯反射率的表面的方向，并且包含两个步骤。第一步，称为漫反射-镜面反射分离，在镜面不变颜色子空间中初始化表面方向，并在RGB空间中进一步分离漫反射和镜面反射分量。在第二步中，通过首先由于分离而通过求解对数线性回归问题来初始化镜面参数，然后使用Levenberg-Marquardt算法拟合DRM，来细化表面方向。由于在初始化中采用了来自无镜面反射的漫反射的可靠信息，所提出的方法在较少观测的情况下是稳健且可行的。在出现密集非朗伯反射率的像素处，利用来自镜面反射的信号来细化表面方向，并且额外获取的镜面参数对于更多应用（例如数字重光照）可能具有价值。评估了新提出的表面法线细化步骤的有效性，并且通过包含该步骤，估计表面方向的准确性平均提高了约30%。在使用由二十四种不同介电材料反射率组成的合成输入图像的实验中，所提出的方法也被证明是有效的。在五个代表性数据集上与其他九种PS方法的比较进一步证明了所提出方法的有效性。
