Estimation of 3D Faces and Illumination from Single Photographs Using a Bilineaur Illumination Model

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Estimation of 3D Faces and Illumination from Single Photographs Using a Bilineaur Illumination Model

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Title: Estimation of 3D Faces and Illumination from Single Photographs Using a Bilineaur Illumination Model
Author: Lee, Jinho; Machiraju, Raghu; Pfister, Hanspeter; Moghaddam, Baback

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Citation: Lee, Jinho, Raghu Machiraju, Hanspeter Pfister, and Baback Moghaddam. 2005. Estimation of 3D faces and illumination from single photographs using a bilineaur illumination model. In Proceedings Rendering Techniques 2005: Eurographics symposium on rendering: June 29 - July 01, 2005, Konstanz, Germany, ed. K. Bala, and P. Dutré, 73-82. Aire-la-Ville: Eurographics Association.
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Abstract: 3D Face modeling is still one of the biggest challenges in computer graphics. In this paper we present a novel framework that acquires the 3D shape, texture, pose and illumination of a face from a single photograph. Additionally, we show how we can recreate a face under varying illumination conditions. Or, essentially relight it. Using a custom-built face scanning system, we have collected 3D face scans and light reflection images of a large and diverse group of human subjects . We derive a morphable face model for 3D face shapes and accompanying textures by transforming the data into a linear vector sub-space. The acquired images of faces under variable illumination are then used to derive a bilinear illumination model that spans 3D face shape and illumination variations. Using both models we, in turn, propose a novel fitting framework that estimates the parameters of the morphable model given a single photograph. Our framework can deal with complex face reflectance and lighting environments in an efficient and robust manner. In the results section of our paper, we compare our methods to existing ones and demonstrate its efficacy in reconstructing 3D face models when provided with a single photograph. We also provide several examples of facial relighting (on 2D images) by performing adequate decomposition of the estimated illumination using our framework.
Published Version: doi:10.2312/EGWR/EGSR05/073-082
Other Sources: http://gvi.seas.harvard.edu/sites/all/files/egsr05.pdf
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:4138745
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