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|a Bousseau, Adrien
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|a Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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|a Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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|a Durand, Fredo
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|a Durand, Fredo
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|a Paris, Sylvain
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|a Durand, Fredo
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|a User-assisted intrinsic images
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|b Association for Computing Machinery,
|c 2012-07-26T19:51:43Z.
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|z Get fulltext
|u http://hdl.handle.net/1721.1/71855
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|a For many computational photography applications, the lighting and materials in the scene are critical pieces of information. We seek to obtain intrinsic images, which decompose a photo into the product of an illumination component that represents lighting effects and a reflectance component that is the color of the observed material. This is an under-constrained problem and automatic methods are challenged by complex natural images. We describe a new approach that enables users to guide an optimization with simple indications such as regions of constant reflectance or illumination. Based on a simple assumption on local reflectance distributions, we derive a new propagation energy that enables a closed form solution using linear least-squares. We achieve fast performance by introducing a novel downsampling that preserves local color distributions. We demonstrate intrinsic image decomposition on a variety of images and show applications.
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|a National Science Foundation (U.S.) (NSF CAREER award 0447561)
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|a Institut national de recherche en informatique et en automatique (France) (Associate Research Team "Flexible Rendering")
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|a Microsoft Research (New Faculty Fellowship)
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|a Alfred P. Sloan Foundation (Research Fellowship)
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|a Quanta Computer, Inc. (MIT-Quanta T Party)
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|a en_US
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|a Article
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|t Proceedings of ACM SIGGRAPH Asia 2009, ACM Transactions on Graphics (TOG)
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