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Light source position and reflectance estimation from a single view without the distant illumination assumption

机译:无需遥远照明假设即可从单个视图估计光源位置和反射率

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Several techniques have been developed for recovering reflectance properties of real surfaces under unknown illumination. However, in most cases, those techniques assume that the light sources are located at infinity, which cannot be applied safely to, for example, reflectance modeling of indoor environments. In this paper, we propose two types of methods to estimate the surface reflectance property of an object, as well as the position of a light source from a single view without the distant illumination assumption, thus relaxing the conditions in the previous methods. Given a real image and a 3D geometric model of an object with specular reflection as inputs, the first method estimates the light source position by fitting to the Lambertian diffuse component, while separating the specular and diffuse components by using an iterative relaxation scheme. Our second method extends that first method by using as input a specular component image, which is acquired by analyzing multiple polarization images taken from a single view, thus removing its constraints on the diffuse reflectance property. This method simultaneously recovers the reflectance properties and the light source positions by optimizing the linearity of a log-transformed Torrance-Sparrow model. By estimating the object's reflectance property and the light source position, we can freely generate synthetic images of the target object under arbitrary lighting conditions with not only source direction modification but also source-surface distance modification. Experimental results show the accuracy of our estimation framework.
机译:已经开发了几种技术来恢复未知照明下真实表面的反射特性。但是,在大多数情况下,那些技术假定光源位于无穷远处,这不能安全地应用于例如室内环境的反射率建模。在本文中,我们提出了两种方法来估计对象的表面反射特性,以及在没有远处照明假设的情况下从单个视图估计光源的位置,从而放宽了先前方法中的条件。给定具有镜面反射作为输入的对象的真实图像和3D几何模型,第一种方法通过拟合朗伯散射分量来估计光源位置,同时使用迭代松弛方案将镜面和散射分量分开。我们的第二种方法通过使用镜面反射分量图像作为输入来扩展第一种方法,该镜面反射分量图像是通过分析从单个视图获取的多个偏振图像而获得的,从而消除了其对漫反射特性的限制。该方法通过优化对数变换的Torrance-Sparrow模型的线性度,同时恢复了反射率属性和光源位置。通过估计物体的反射特性和光源位置,我们不仅可以改变光源方向,而且可以改变光源表面距离,从而可以在任意光照条件下自由生成目标物体的合成图像。实验结果表明了我们估计框架的准确性。

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