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In this paper, we present an unsupervised method for segmenting the illuminant regions and estimating the illumination power spectrum from a single image of a scene lit by multiple light sources. Here, illuminant region segmentation is cast as a probabilistic clustering problem in the image spectral radiance space. We formulate the problem in an optimization setting, which aims to maximize the likelihood...
A method is proposed for estimating two illuminant spectral power distributions from the highlights of overlapping illuminants on an object. It was assumed in most previous studies that specular highlights on object surfaces are caused by a single light source, or by separate multiple light sources. In this paper, we assume that two highlights from different light sources are overlapped on object...
This paper discusses a method to estimate 3D shape, color and specular components using an image scanner. This shape reconstruction method is based on the photometric stereo method, but we consider multiple linear light sources in the shape reconstruction algorithm. In our previous methods, color and specular estimation needs many images. Therefore, we propose a new method to obtain the optimal light...
This paper proposes a method for estimating the illuminant spectral power distributions and their positional relationship of multiple light sources under a complex illumination environment. A multiband camera system is used for capturing spectral images of dielectric objects in a scene. Specular highlights are used as a clue for estimating the light source information, which are detected on curved...
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