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Illumination distribution from brightness in shadows: Adaptive estimation of illumination distribution with unknown reflectance properties in shadow regions

机译:阴影中亮度的照明分布:阴影区域中具有未知反射特性的照明分布的自适应估计

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This paper describes a new method for estimating the illumination distribution of a real scene from a radiance distribution inside shadows cast by an object in the scene. First, the illumination distribution of the scene is approximated by discrete sampling of an extended light source. Then the illumination distribution of the scene is estimated from a radiance distribution inside shadows cast by an object of known shape onto another object in the scene. Instead of assuming any particular reflectance properties of the surface inside the shadows, both the illumination distribution of the scene and the reflectance properties of the surface are estimated simultaneously, based on iterative optimization framework. In addition, this paper introduces an adaptive sampling of the illumination distribution of a scene. Rather than using a uniform discretization of the overall illumination distribution, we adaptively increase sampling directions of the illumination distribution based on the estimation at the previous iteration. Using the adaptive sampling framework, we are able to estimate overall illumination more efficiently by using fewer sampling directions. The proposed method is effective for estimating an illumination distribution even under a complex illumination environment.
机译:本文介绍了一种从场景中物体投射的阴影内部的辐射度分布估算真实场景的照明分布的新方法。首先,通过扩展光源的离散采样来估算场景的照明分布。然后,根据已知形状的对象投射到场景中另一个对象的阴影内部的辐射度分布,估算场景的照明分布。基于迭代优化框架,可以同时估算场景的照度分布和表面的反射率特性,而不是假设阴影内部的表面具有任何特定的反射率特性。此外,本文介绍了场景照度分布的自适应采样。而不是使用整个照明分布的均匀离散,我们根据前一次迭代的估计来自适应地增加照明分布的采样方向。使用自适应采样框架,我们可以通过使用更少的采样方向来更有效地估计整体照明。即使在复杂的照明环境下,所提出的方法对于估计照明分布也是有效的。

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