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  Reflectance from Images: A Model-Based Approach for Human Faces

Fuchs, M., Blanz, V., Lensch, H. P. A., & Seidel, H.-P. (2005). Reflectance from Images: A Model-Based Approach for Human Faces. IEEE Transactions on Visualization and Computer Graphics, 11, 296-305.

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Copyright 2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reyuse any copyrighted component of this work in other works must be obtained from the IEEE.
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Fuchs, Martin1, Author           
Blanz, Volker1, Author           
Lensch, Hendrik P. A.1, Author           
Seidel, Hans-Peter1, Author           
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1Computer Graphics, MPI for Informatics, Max Planck Society, ou_40047              

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 Abstract: In this paper, we present an image-based framework that acquires the reflectance properties of a human face. A range scan of the face is not required. Based on a morphable face model, the system estimates the 3D shape, and establishes point-to-point correspondence across images taken from different viewpoints, and across different individuals' faces. % This provides a common parameterization of all reconstructed surfaces that can be used to compare and transfer BRDF data between different faces. Shape estimation from images compensates deformations of the face during the measurement process, such as facial expressions. In the common parameterization, regions of homogeneous materials on the face surface can be defined a-priori. We apply analytical BRDF models to express the reflectance properties of each region, and we estimate their parameters in a least-squares fit from the image data. For each of the surface points, the diffuse component of the BRDF is locally refined, which provides high detail. % We present results for multiple analytical BRDF models, rendered at novel orientations and lighting conditions.

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Language(s): eng - English
 Dates: 2006-04-132005
 Publication Status: Issued
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 Rev. Type: Peer
 Identifiers: eDoc: 279056
Other: Local-ID: C125675300671F7B-40B8185E1038C225C1256FAF003BD72B-Fuchs2005a
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Title: IEEE Transactions on Visualization and Computer Graphics
Source Genre: Journal
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Pages: - Volume / Issue: 11 Sequence Number: - Start / End Page: 296 - 305 Identifier: ISSN: 1077-2626