Texture Replacement in Real Images

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Texture Replacement in Real Images
Texture replacement in real images has many applications, such as interior design, digital movie making and computer graphics. The goal is to replace some specified texture patterns in an image while preserving lighting effects, shadows and occlusions. To achieve convincing replacement results we have to detect texture patterns and estimate lighting map from a given image. Near regular planar texture patterns are considered in this paper. Given a sample texture patch, a standard tile is computed. Candidate texture regions are determined by mutual information between the standard tile and each image patch. Regions with high mutual information scores are used to estimate the admissible lighting distributions, which is represented by cached statistics. Spatial lighting change constraints are represented by a Markov random field model. Maximum a posteriori estimation of the texture segmentation and lighting map is solved in a stochastic annealing fashion, namely, the Markov Chain Monte Ca...
Yanghai Tsin, Yanxi Liu, Visvanathan Ramesh
Added 12 Oct 2009
Updated 29 Oct 2009
Type Conference
Year 2001
Where CVPR
Authors Yanghai Tsin, Yanxi Liu, Visvanathan Ramesh
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