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A practical single image based approach for estimating illumination distribution from shadows

机译:一种实用的基于单个图像的方法,用于估计阴影的照明分布

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This paper presents a practical method that estimates illumination distribution from shadows where the shadows are assumed to be cast on a textured, Lambertian surface. Previous methods usually require that the reflectance property of the surface be constant or uniform, or need an additional image to cancel out the effects of varying albedo of the textured surface. We deal with an estimation problem for which surface albedo information is not available. In this case, the estimation problem corresponds to an underdetermined one. We show that combination of regularization by correlation and some user-specified information can be a practical method for solving the problem. In addition, as an optimization tool for solving the problem, we develop a constrained nonnegative quadratic programming (NNQP) technique into which not only regularization but also user-specified information are easily incorporated. We test and validate our method on both synthetic and real images and present some experimental results.
机译:本文提出了一种实用的方法,可以从阴影中估计照明分布,其中假定阴影被投射在带纹理的朗伯表面上。先前的方法通常要求表面的反射率特性是恒定或均匀的,或者需要附加图像以抵消纹理化表面的反射率变化的影响。我们处理表面反照率信息不可用的估计问题。在这种情况下,估计问题对应于未确定的问题。我们表明,通过相关性和某些用户指定的信息进行正则化的组合可以解决该问题。此外,作为解决问题的优化工具,我们开发了一种受约束的非负二次规划(NNQP)技术,该技术不仅可以轻松地包含正则化功能,而且可以轻松地包含用户指定的信息。我们在合成图像和真实图像上测试并验证了我们的方法,并提出了一些实验结果。

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