The standard photometric stereo model makes several assumptions that are rarely verified in experimental datasets. In particular, the observed object should behave as a Lambertian reflector and the light sources should be positioned at an infinite distance from it, along a known direction. Even when Lambert's law is approximately fulfilled, an accurate assessment of the relative position between the light source and the target is often unavailable in real situations. The Hayakawa procedure is a computational method for estimating such information directly from the data images. It occasionally breaks down when some of the available images excessively deviate from ideality. This is generally due to observing a non Lambertian surface, or illuminating it from a close distance, or both. Indeed, in narrow shooting scenarios, typical, e.g., of archaeological excavation sites, it is impossible to position a flashlight at a sufficient distance from the observed surface. It is then necessary to understand if a given dataset is reliable and which images should be selected to better reconstruct the target. In this paper, we propose some algorithms to perform this task and explore their effectiveness.

翻译：标准光度立体模型包含若干假设，但这些假设在实验数据集中鲜少得到验证。具体而言，观测物体需满足朗伯反射特性，且光源应位于无穷远处并沿已知方向照射。即便朗伯定律近似成立，实际场景中光源与目标相对位置的精确评估往往难以实现。早川算法（Hayakawa procedure）作为一种计算方法，可直接从图像数据中估计此类信息。但当部分可用图像严重偏离理想状态时——通常源于观测非朗伯表面、近距离照明或两者兼有——该算法可能失效。在狭窄拍摄场景（如考古发掘现场的典型情境）中，无法将光源置于距观测表面足够远的位置。因此，必须判定给定数据集的可靠性，并筛选出更利于目标重建的图像。本文提出若干算法完成该任务，并验证其有效性。