User Assisted Intrinsic Images
Abstract
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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intrinsic_main.pdf (23.53 Mo)
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baby_shading.png (610.03 Ko)
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baby_reflectance.png (394.15 Ko)
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baby_scribbles.png (636.13 Ko)
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house_illumination.png (665.31 Ko)
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house_reflectance.png (1.5 Mo)
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house_scribbles.png (1.8 Mo)
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intrinsic_video.mov (52.08 Mo)
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paper_illumination.png (500.34 Ko)
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paper_reflectance.png (420.93 Ko)
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paper_scribbles.png (1.65 Mo)
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teaser.png (751.25 Ko)
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