Variational Shape and Reflectance Estimation under Changing Light and Viewpoints

Neil Birkbeck 1 Dana Cobzas 1 Peter Sturm 2 Martin Jägersand 1
2 MOVI - Modeling, localization, recognition and interpretation in computer vision
GRAVIR - IMAG - Graphisme, Vision et Robotique, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : Fitting parameterized 3D shape and general reflectance models to 2D image data is challenging due to the high dimensionality of the problem. The proposed method combines the capabilities of classical and photometric stereo, allowing for accurate reconstruction of both textured and non-textured surfaces. In particular, we present a variational method implemented as a PDE-driven surface evolution interleaved with reflectance estimation. The surface is represented on an adaptive mesh allowing topological change. To provide the input data, we have designed a capture setup that simultaneously acquires both viewpoint and light variation while minimizing self-shadowing. Our capture method is feasible for real-world application as it requires a moderate amount of input data and processing time. In experiments, models of people and everyday objects were captured from a few dozen images taken with a consumer digital camera. The capture process recovers a photo-consistent model of spatially varying Lambertian and specular reflectance and a highly accurate geometry.
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Conference papers
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https://hal.inria.fr/inria-00387143
Contributor : Peter Sturm <>
Submitted on : Sunday, May 24, 2009 - 2:05:45 PM
Last modification on : Sunday, November 4, 2018 - 7:54:02 AM

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  • HAL Id : inria-00387143, version 1

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Neil Birkbeck, Dana Cobzas, Peter Sturm, Martin Jägersand. Variational Shape and Reflectance Estimation under Changing Light and Viewpoints. European Conference on Computer Vision, May 2006, Graz, Austria. pp.536-549. ⟨inria-00387143⟩

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